WO2008072739A1 - 視聴傾向管理装置、システム及びプログラム - Google Patents
視聴傾向管理装置、システム及びプログラム Download PDFInfo
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- WO2008072739A1 WO2008072739A1 PCT/JP2007/074156 JP2007074156W WO2008072739A1 WO 2008072739 A1 WO2008072739 A1 WO 2008072739A1 JP 2007074156 W JP2007074156 W JP 2007074156W WO 2008072739 A1 WO2008072739 A1 WO 2008072739A1
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- viewing tendency
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Classifications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/16—Analogue secrecy systems; Analogue subscription systems
- H04N7/173—Analogue secrecy systems; Analogue subscription systems with two-way working, e.g. subscriber sending a programme selection signal
- H04N7/17309—Transmission or handling of upstream communications
- H04N7/17318—Direct or substantially direct transmission and handling of requests
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/40—Information retrieval; Database structures therefor; File system structures therefor of multimedia data, e.g. slideshows comprising image and additional audio data
- G06F16/43—Querying
- G06F16/435—Filtering based on additional data, e.g. user or group profiles
- G06F16/436—Filtering based on additional data, e.g. user or group profiles using biological or physiological data of a human being, e.g. blood pressure, facial expression, gestures
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/40—Information retrieval; Database structures therefor; File system structures therefor of multimedia data, e.g. slideshows comprising image and additional audio data
- G06F16/43—Querying
- G06F16/435—Filtering based on additional data, e.g. user or group profiles
- G06F16/437—Administration of user profiles, e.g. generation, initialisation, adaptation, distribution
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
- H04N21/25—Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication, learning user preferences for recommending movies
- H04N21/251—Learning process for intelligent management, e.g. learning user preferences for recommending movies
- H04N21/252—Processing of multiple end-users' preferences to derive collaborative data
Definitions
- the present invention evaluates a viewer response to content based on a viewer's physiological response.
- It relates to a technique for analyzing viewing tendency from the evaluation result.
- This video content evaluation apparatus takes an eyeball of a viewer who views video content with an infrared camera, binarizes the eyeball image signal to obtain eye movement data, and displays a graph of the eye movement data on the time axis. The video content is evaluated by displaying it on the display.
- Patent Document 1 Japanese Patent Application Laid-Open No. 2004-282471
- the video content evaluation apparatus accumulates information that evaluates the video content and, for example, generates information that the viewer likes based on the accumulated information, the preference information is transmitted to the viewer. It can be useful information with high utility value even for a video content provider.
- the video content evaluation apparatus described above is merely an apparatus for evaluating video content by measuring a passive response of a viewer to unilaterally presented video content. Therefore, based on the evaluation information, it is not intended to generate and present useful information that is highly useful to viewers and content providers.
- the present invention has been made to solve the above-described problems, and an object of the present invention is to obtain a complex tendency such as data input and key operation by obtaining a viewing tendency with respect to content.
- the present invention measures and analyzes the physiological response information (for example, eye movement) of the viewer when the viewer is watching the content, calculates the interest / degree of interest in the content, and determines the viewing tendency. It is characterized by analyzing and generating information for presentation to viewers and content providers from the analysis results. It should be noted that generating information for presentation includes selecting necessary contents from a plurality of contents and information.
- the viewing tendency management device is based on the physical reaction information of the viewer who views the content, the interest “interest for calculating the interest level”, the interest level calculation unit, and the interest / interest
- a viewing tendency analysis unit that analyzes the change of interest / interest degree calculated by the degree calculation unit on a time axis and generates information indicating a viewing tendency when the viewer views the content; and the viewing tendency analysis unit And an information processing unit for generating presentation information from the viewing tendency information generated by.
- a viewing tendency management system includes a content distribution device that distributes content requested by a viewer, a terminal device that receives the distributed content and displays the content on a display, and a physiological reaction of the viewer Physiological reaction measuring device that measures the content, and viewing tendency that obtains physiological response information of the viewer who views the content displayed on the display device from the physiological response measuring device, analyzes the viewing tendency, and generates presentation information
- a viewing tendency management system in which a management device is connected to each other via a communication network, wherein the content distribution device reads content according to a viewer's request from a content database in which a plurality of content is stored, and the terminal device A distribution unit that distributes to the viewer, and that the terminal device has viewed the content displayed on the display by the viewer.
- the physiologic response measuring device includes a transmitting unit that inputs the physiological response information and transmits the physiological response information to the viewing tendency management device. Receive and respond to content based on this physiological response information Interest ⁇ Interest calculation to calculate the interest level and the interests calculated by the interest and interest level calculation unit are analyzed on the time axis and the viewer views the content. And an information processing unit that generates presentation information from the viewing tendency information generated by the viewing tendency analysis unit.
- a viewing tendency management program is a program for managing a viewing tendency of a viewer by a device for inputting a response of a viewer who is viewing the content, and a computer constituting the device.
- the procedure to calculate the interest and interest level of the content and the change of the calculated interest It is characterized in that a process for generating information indicating a viewing tendency when viewing and a process for generating presentation information from the generated viewing tendency information are executed.
- the present invention by obtaining the viewing tendency of content, it is highly useful and useful for viewers or content providers who do not perform complicated operations such as data input operations. It is possible to realize a viewing tendency management device, system and program capable of presenting information.
- FIG. 1 is a block diagram showing an overall configuration of a viewing tendency management system according to an embodiment of the present invention.
- FIG. 2 is a block diagram showing a configuration of the viewing tendency management server in FIG.
- FIG. 3 is a flowchart showing an initial process.
- FIG. 4 is a diagram showing a flow of information in the process of FIG.
- FIG. 5 is a flowchart showing viewing tendency analysis processing.
- FIG. 7 is a diagram showing area division of a web page.
- FIG. 8 is a diagram showing the transition of interest / interest level classified by region.
- FIG. 9 is a flowchart showing recommended content presentation processing.
- FIG. 10 is a diagram showing a flow of information in the process of FIG.
- FIG. 11 is a diagram showing screen transition in recommended content presentation processing.
- FIG. 12 is a flowchart showing attention object information presentation processing.
- FIG. 13 is a diagram showing screen transition in attention object information presentation processing.
- FIG. 14 is a flowchart showing viewing tendency influence degree information presentation processing.
- FIG. 15 is a diagram for explaining viewing tendency influence degree information presentation processing.
- FIG. 16 is a block diagram showing an overall configuration of a viewing tendency management system for explaining a presentation content switching process.
- FIG. 17 Interest for explaining the presented content switching process.
- FIG. 18 is a flowchart showing presented content switching processing.
- FIG. 19 is a diagram for explaining a presentation content determination process in the flowchart of FIG. 18.
- FIG. 20 is a flowchart showing attention level determination processing.
- FIG. 21 is a diagram showing a transition of interest / interest level for explaining the attention level determination process.
- FIG. 22 is a diagram showing objects for explaining attention level determination processing.
- FIG. 23 is a flowchart showing a favorable feeling / disgusting judgment process.
- FIG. 24 is a flowchart showing an impression evaluation process.
- FIG. 25 is a flowchart showing designated area emotional effect processing.
- FIG. 26 Interests are diagrams for explaining the interest duration.
- FIG. 27 is a diagram showing an example of an interest level of interest in an object in which disgust and an object in which favorable feeling are generated.
- FIG. 1 is a block diagram showing the overall configuration of a viewing tendency management system according to an embodiment of the present invention.
- This viewing tendency management system 2 inputs the physiological response (eye movement) information and viewer response to the content by the viewer 1 who is the viewer, calculates the interest of the viewer 1 for the content, and calculates the interest level. The viewing tendency is analyzed based on the degree of interest, and useful information is generated and presented to the viewer 1 or the content provider from the viewing tendency.
- the viewing tendency management system 2 includes a display 11 for presenting content and preference information to the viewer 1, an input device 12 such as a mouse that is input by the viewer 1 for a viewer response, and an infrared lamp.
- the IR light 14 captures the eye movement of the viewer 1 Physiological reaction measurement device 13 including a camera, the input unit that displays the content on the display 11 and inputs physiological response information and the viewer response from the input device 12, And viewing tendency management Content presentation 'physiological response' viewer response measuring device (terminal device) equipped with a transmission unit that sends physiological response information etc.
- this content presentation ⁇ physiological reaction ⁇ viewer response measurement Viewing trend management server 100 that receives physiological response information from the device 10 and manages the viewing trend of the viewer 1, physiological response viewer response database 101, reference content data Database 102, personal attributes / viewing tendency database 103, presentation content database 106 with stored moving image content, content read from presentation content database 106 according to the request from viewer 1 Physical reaction ⁇ Content distribution server 105 with a distribution unit that distributes to the viewer response measuring device 10, content presentation 'physiological reaction' viewer response measuring device 10, viewing tendency management server 100, and content distribution server 105
- the network 104 is configured to be connected to each other by network communication such as the Internet or a LAN.
- the content presentation / physiological reaction / viewer response measuring apparatus 10 reads the content from the presentation content database 106 via the content distribution server 105 and the network 104 and displays the content on the display 11.
- a viewer response according to the operation of the input device 12 by the viewer 1 is input, and the physiological reaction information that is an eyeball image of the viewer 1 is input from the physiological response measuring device 13 in synchronization with this.
- the viewer response and physiological response information are stored in the physiological response and viewer response database 101 via the network 104 and the viewing tendency management server 100.
- the content presentation / physiological reaction / viewer response measuring apparatus 10 receives the preference information of the viewer 1 generated by the viewing tendency management server 100 and displays it on the display 11.
- FIG. 2 is a block diagram showing a configuration of the viewing tendency management server 100 shown in FIG.
- This viewing tendency management server 100 includes a content reading and presentation unit 110, an information capturing unit 120, an interest 'interest level calculation unit 130, a viewing tendency An analysis unit 140 and an information processing unit 150 are provided.
- the viewing tendency management server 100 is connected to a physiological response “viewer response database 101, a reference content database 102, and a personal attribute“ viewing tendency database 103 ”to write and read various information.
- the physiological response 'viewer response database 101 sequentially stores the physiological response information and the viewer response to the viewer's content.
- the viewer's interest and interest in the content is sequentially stored, and viewing tendency information such as viewing tendency vectors is also stored in sequence.
- the viewing tendency management server 100 performs a series of processes (1) to (4) below.
- the interest level and the viewer tendency vector for the reference content are calculated and stored in the personal attribute / viewing tendency database 103, and the personal attribute information c of the viewer is collected.
- Stored in the database 103 such as personal attributes' viewing tendency.
- the reference content refers to content for collecting auxiliary data that can be used to determine the viewing tendency and viewing preference of individual viewers. For example, an image without a pattern, an image in which a symbol is moved or an image of a landscape, or any content existing on a network provided for them can be used.
- location information of the content is recorded in the reference content database 102.
- the personal attribute information c is information such as the viewer's individual occupation, occupation, gender, age, married / unmarried, past address, current address, annual income, and household composition.
- Physiological response information a and viewer response b for the content viewed by the viewer are stored in the physiological response / viewer response database 101.
- the physiological response information a refers to information on the eye movement of the viewer who is watching the content.
- the viewer response is information such as the mouse curl position (coordinates) and mouse click position (coordinates) specified by the operation of the input device 12 in synchronization with the content being viewed by the viewer! / Uh.
- Interest in content viewed by viewers ⁇ Calculate the degree of interest and personal attributes ⁇ Viewing inclination Accumulate in the second database 103.
- the average value of interest / interest per unit time is calculated to obtain the viewing tendency vector, and the average value of interest and the viewing tendency vector are stored in the personal attribute / viewing tendency database 103 as viewing tendency information. .
- viewing tendency information is sequentially stored for each combination of viewer and content. The viewing tendency information accumulated in this way is used to generate information that matches the viewer's preference.
- the viewing tendency information such as the viewing tendency vector generated by the viewing tendency process, information to be presented to the viewer, content provider, etc. is generated.
- FIG. 3 is a flowchart showing the initial processing
- FIG. 4 is a diagram showing the flow of information in the initial processing.
- reference content is stored in advance in reference content database 102.
- the content reading / presenting unit 110 reads the reference content from the reference content database 102 and transmits it to the content presentation / physiological reaction / viewer response measuring device 10 via the network 104, and the time such as the frame number of the reference content.
- the information is output to the information fetching unit 120.
- the transmitted reference content is displayed on the display 11 by the content presentation “physiological reaction” viewer response measuring device 10 (step S301).
- Information fetching unit 120 inputs time information of reference content from content reading / presenting unit 110.
- the information capturing unit 120 displays the content presentation / physiological reaction / viewer response measuring apparatus 10 and the network 104. Enter physiological response information a and viewer response b. Then, the information capturing unit 120 generates synchronization information based on the time information of the input content so that the physiological response information a and the viewer response b can be associated with the reference content.
- Interest / interest level calculator 130 inputs physiological response information a, viewer response b, and synchronization information from information capture unit 120 (step S302), calculates the pupil diameter of viewer 1, The interest level and the viewpoint position are calculated, and the interest level, the interest position, the viewpoint position, and the synchronization information are stored in the personal attribute / viewing tendency database 103 and output to the viewing tendency analysis unit 140 (step S303). Specifically, the interest / interest level calculation unit 130 extracts a pupil image from the physiological response information a, and calculates the viewpoint position based on the center position of the pupil, position information on the screen set in advance, and the like.
- gaze movement data such as the movement speed of the visual point and the trajectory of the visual point can also be obtained by calculating the visual point position with time change.
- the pupil diameter is calculated based on the extracted pupil image.
- the blink occurrence frequency can be calculated based on the temporal change of the extracted pupil image, and the number of blinks can be obtained.
- the pupil diameter change speed and acceleration can be obtained.
- the interest / interest level calculation unit 130 calculates the interest level as shown below using the calculated pupil diameter.
- the interest / interest level calculator 130 may calculate the interest level based on information obtained from a pupil image such as eye movement data, blink frequency, or pupil size.
- P (t) is the pupil diameter at time t
- I (t) is the interest-interest level at time t
- the interest / interest level calculator 130 first calculates a high-frequency component for the pupil diameter P (t). In order to remove measurement noise, low-pass filter processing is performed by performing operations such as moving average.
- Pmax is the maximum value of pupil diameter P (t) in the measurement data sequence within a predetermined time
- Pmin is the minimum value
- th is the threshold value.
- an intermediate value between the maximum value Pmax and the minimum value Pmin is used, for example, as in the following equation.
- the interest / interest level calculation unit 130 determines whether or not the calculated blink occurrence frequency is larger than a preset threshold value, and continuously becomes larger than the threshold value! /
- the interest / interest level I (t) may be forced to 0 for the continuous blinking interval.
- the viewing tendency analysis unit 140 inputs the interest / interest level, viewpoint position, and synchronization information from the interest / interest level calculation unit 130 or the personal attribute / viewing trend database 103 to calculate a viewing trend vector and the like. Then, the synchronization information of the reference content and the viewing tendency vector are stored in the personal attribute-viewing tendency database 103 (step S304). Details of the method of calculating the viewing tendency vector will be described later.
- the information capturing unit 120 inputs the personal attribute information c through the network 104 by the operation of the input device 12 by the viewer 1, and stores the personal attribute information c in the database 103 such as personal attribute. S 305).
- physiological response information / viewer response accumulation processing will be described. Through this process, physiological response information and viewer responses to the content presented to the viewer 1 are accumulated in the physiological response-viewer response database 101.
- content distribution server 105 reads the content from presentation content database 106 and distributes it to content presentation “physiological reaction” viewer response measuring apparatus 10 via network 104.
- the distributed content is displayed on the display 11 by the content presentation / physiological reaction / viewer response measuring device 10.
- the content reading and presentation unit 110 of the viewing tendency management server 100 inputs time information such as the frame number of the content via the network 104, and the information capturing unit Output to 120.
- the information capturing unit 120 inputs time information of content from the content reading / presenting unit 110.
- the physiological response information a and the viewer response b are input via the network 104. Then, the information capturing unit 120 generates synchronization information based on the time information of the input content so that the physiological response information a and the viewer response b can be associated with the content. Then, the information capturing unit 120 accumulates the physiological response information a, the viewer response b, and the synchronization information in the physiological response / viewer response database 101.
- FIG. 5 is a flowchart showing the viewing tendency analysis processing.
- (2) physiological response information 'viewer response accumulation process described above causes information capture unit 120 to send physiological response information a, viewer response b, and synchronization information to physiological response-viewer response.
- the information is stored in the database 101 and the information is output to the interest / interest degree calculation unit 130.
- the interest / interest level calculator 130 inputs the physiological response information a, the viewer response b, and the synchronization information from the information capture unit 120 or the physiological response / viewer response database 101, and calculates the pupil diameter ( In step S501), the interest / interest level is calculated from the pupil diameter, and the interest 'interest level, viewpoint position, and synchronization information are output to the viewing tendency analysis unit 140 and stored in the database 103 such as personal attributes / viewing tendency ( Step S502). Specifically, as described above, the interest / interest degree calculation unit 130 extracts the pupil image from the physiological response information a and calculates the viewpoint position. Also, gaze movement data such as viewpoint movement speed and viewpoint trajectory is obtained, and the pupil diameter is calculated based on the pupil image.
- the blink occurrence frequency is calculated based on the temporal change of the extracted pupil image, and the number of blinks is obtained. Then, using the calculated pupil diameter, the interest / interest level calculator 130 calculates the interest level as shown in the above-described equation (1).
- the viewing tendency analysis unit 140 inputs the interest / interest level and synchronization information from the interest / interest level calculation unit 130 or the personal attribute / viewing trend database 103, calculates the viewing trend vector, etc., and synchronizes the content. Information and viewing tendency vectors, etc. The data is stored in the database 103 (step S503). As a result, in the personal attribute 'viewing tendency database 103, viewing tendency vectors and the like are stored independently for each viewer and for each content viewed by the viewer (for each combination of viewer and content).
- the viewing tendency vector calculation method will be described separately for the case where the content is a moving image and the case of a web page or the like.
- the viewing tendency analysis unit 140 performs the time variation of the interest level in the time interval j corresponding to the continuous frames (sequence, scene, cut, etc.) of the moving image media I (t)
- the average value per unit time is calculated as follows.
- the time interval j corresponding to the sequence, scene, cut, etc. is set in advance by manual input or the like.
- the viewing tendency analysis unit 140 converts the viewing tendency vector of the viewer X into the interest / interest level for each continuous time interval [0, n]! Set by a sequence of average values per hour.
- Q x (q ,, i ⁇ ( ⁇ i ⁇ n) (5)
- X is a number that identifies the viewer.
- the viewing tendency vector in this case is the average value of the interest level per unit time in each area of the web page.
- the viewing tendency analysis unit 140 first identifies and labels the viewpoint stay area based on the viewpoint position information in the interest / interest degree I (t) shown in FIG.
- the viewpoint stay area in time interval j1-4 is labeled as A (AO)
- the viewpoint stay area in interval j1-3 is labeled as B (B0)
- This labeling is performed according to the magnitude relationship between the coordinate values of the four vertices of the rectangle that defines each region and the coordinate values of the viewpoint at that time.
- the residence time in each time zone dBO, dBl, dB2,..., DBn—1 is ⁇ , TBI, TB2, TB3,.
- Interest ⁇ Average value of interest level per unit time qB is as follows.
- TB is the total time that the viewpoint stays in area B and is calculated as follows.
- the viewing tendency analysis unit 140 converts the viewing tendency vector of the viewer X into the interest for each area of the divided web page.
- x is a number that identifies the viewer.
- the viewing tendency analysis unit 140 calculates an average value per unit time of the interest level of the content scene for the processing of the viewing tendency influence processing unit 153 in the information processing unit 150 described later.
- the average value is calculated as the above-described formulas (3) and (4), and is stored in the personal attribute / viewing tendency database 103 as viewing direction information and is output to the information processing unit 150.
- the viewing tendency analysis unit 140 performs processing of a favorable feeling / aversion determination processing unit 156, an impression evaluation processing unit 157, and a designated area emotional (emotion) effect processing unit 158 in the information processing unit 150 described later.
- the interest / degree of interest in a predetermined area is stored in the personal attribute / viewing tendency database 103 as viewing tendency information, and is output to the information processing unit 150.
- the information processing unit 150 has a function of generating presentation information based on viewing tendency information such as a viewing tendency title, and includes recommended content processing means 151, attention object information processing means 152, A viewing tendency influence degree processing means 153, a presentation content switching processing means 154, a degree-of-interest determination processing means 155, a favorable feeling / aversion judgment processing means 156, an impression evaluation processing means 157, and a designated area emotional effect processing means 158 are provided.
- the presentation information generated by the recommended content processing means 151 is recommended content, and the recommended content processing means 151 identifies viewers with similar viewing trends for the currently viewed content based on the viewing tendency vector! The content associated with the content being viewed is identified, the content of the related content is also identified with the content of interest and interest of similar viewers, and the content is presented to the viewing viewer 1. Further, the presentation information generated by the attention object information processing means 152 is attention object information, and the attention object information processing means 152 identifies a region of high interest level based on the viewing tendency vector, The object contained in is identified, and information about the object is presented to the viewing viewer 1.
- the presentation information generated by the viewing tendency influence degree processing unit 153 is the viewing tendency influence degree information
- the viewing tendency influence degree processing means 1 53 has two consecutive scenes in which the immediately preceding scene is the subsequent scene. The degree of influence on the viewing tendency is calculated, and the degree of influence is presented to the content provider as viewing tendency influence information.
- the presentation information generated (changed) by the presentation content switching processing unit 154 is the presentation content, and the presentation content switching processing unit 154 determines the presentation content based on viewing tendencies by a plurality of viewers 1, and this determination The presented content is presented to multiple viewers 1 as presentation information.
- the presentation information generated by the attention level determination processing unit 155 is attention level information on the analysis target in the screen, and the attention level determination processing unit 155 includes the interest / interest level and the viewer 1 of the analysis target. Based on the response (for example, button press by viewer 1), the degree of attention to the analysis target is determined, and this attention degree information is presented to the content provider as presentation information.
- the presentation information generated by the favorable / disgusting judgment processing means 156 Favorable / disgusting sensitivity, and the favorable / disgusting determination processing means 156 determines whether the object is favorable or disgusting based on the duration of the interest / interesting level that satisfies the predetermined condition for the object to be analyzed.
- the likability and aversion sensitivity are calculated, and the information on the likability and aversion sensitivity is presented to the content provider as presentation information.
- the presentation information generated by the impression evaluation processing means 157 is an impression level indicating the impression degree! /, Which is given to the viewer 1 by the viewer in the screen.
- the impression evaluation processing means 157 is the object to be analyzed.
- the impression degree is calculated by combining the above-mentioned favorable sensitivity and aversion sensitivity, and information on the impression degree is presented to the content provider as presentation information.
- the presentation information generated by the designated area emotional effect processing means 158 is an emotional degree indicating a temporary emotional level caused by the viewer 1 looking at the object in the screen, and is designated area emotional.
- the effect processing means 158 calculates the designated area emotional degree based on the above-mentioned favorable sensitivity and aversion sensitivity to the object to be analyzed and the final operation of the viewer 1 (for example, the mouse operation by the viewer 1).
- the designated area emotional level is presented to the content provider as presentation information.
- Each process of the means 157 and the designated area emotional effect processing means 158 will be described in detail.
- FIG. 9 is a flowchart showing recommended content presentation processing.
- FIG. 10 is a diagram showing a flow of information in the processing of FIG. Assume that the viewer 1 (X) is viewing the content ⁇ presented from the presented content database 106. In this case, the above-described (2) physiological response information / viewer response accumulation processing and (3) viewing tendency analysis processing are performed for the viewer 1 ( ⁇ ) who is viewing the content ⁇ (step S901, S902). That is, the viewing tendency analysis unit 140 views a viewing tendency vector for the content ⁇ being viewed by the viewer 1 (X) (hereinafter, referred to as solid ⁇ nore Qx (a)) Is calculated.
- solid ⁇ nore Qx (a) solid ⁇ nore Qx (a)
- the recommended content processing means 151 of the information processing unit 150 has a preference tendency similar to that of the viewer 1 (X). Identify viewers with orientation. Specifically, the recommended content processing means 151 reads the personal attribute information c of each viewer including the viewer 1 (X) from the personal attribute-viewing tendency database 103 and the personal attribute of the viewer 1 (X). And matching with the personal attributes of other viewers (step S903). For example, for the age in the personal attribute information c, a viewer who has an age within a preset range with respect to the age of the viewer 1 (X) is determined as a matched viewer. Let the matched viewers be Y, Z, U, V, ⁇ .
- the recommended content processing means 151 receives the viewing tendency vector Qx (a) of the viewer 1 (X) from the viewing tendency analysis unit 140, and performs matching from the personal attribute / viewing tendency database 103.
- the viewing tendency vectors Qy ( ⁇ ), Qz ( «) ⁇ , that is,--... >> for the content ⁇ such as the viewer ⁇ , Z, etc. are read, and the viewer ⁇ ⁇ , The degree of correlation between the viewing tendency and the like is calculated (step S904), and similar viewers are identified (step S905).
- the personal attribute / viewing tendency database 103 stores the viewing tendency vector for each viewer's content ⁇ by the above (3) viewing tendency vector calculation and storage processing!
- a method of calculating the viewing tendency correlation will be described.
- the following describes a method for calculating the viewing tendency correlation degree Rv for the same content between the viewer X and the viewer ⁇ .
- the recommended content processing means 151 calculates an inner product between the viewing tendency vector Qx of the viewer X and the viewing tendency vector Qy of the viewer Y, and normalizes this by the number of dimensions of the vector to determine the viewing tendency correlation degree Rv.
- the recommended content processing means 151 may calculate the viewing tendency correlation degree Rv by the following mathematical formula.
- the viewing tendency correlation degree is calculated not only when the content is a moving image but also when it is a web page by the same method.
- the viewing tendency correlation degree Rv may be calculated for a preset time interval that is calculated for each time interval such as a sequence or a scene.
- the recommended content processing unit 151 determines that the viewer is a similar viewer when the correlation degree is equal to or greater than a preset threshold value. Further, when the viewing tendency correlation degree is calculated by the equation (12), it is determined that the viewer is a similar viewer when the correlation degree is equal to or less than a preset threshold value. In this way, the recommended content processing means 151 identifies similar viewers from the matched viewers Z, Z, and the like.
- the recommended content processing means 151 reads a list of content a, b, ... related to the content ⁇ from a related content table (not shown) (step S906), and stores it in the related content a, b, c, etc.
- a content including a scene or the like in which the similar viewer identified in step S905 shows a high interest level is specified as a recommended content and presented to the viewer 1 (step S907).
- the content that is viewed by the viewer 1 is selected from the presented content, and the display screen of the display 11 is switched to the content of interest.
- the related content table content genre, scene in video, etc. Accordingly, related content is set in advance for each content.
- contents a, b,... are set as contents related to the content ⁇ .
- the similarity of keywords in the metadata of content described by a method (not shown), the similarity of color tone in the video, and the like can be used as a determination method.
- the determination of similarity is not limited to these methods.
- the contents of the related content table may be set in advance, or may be updated before or after any step of the recommended content presentation processing (steps S901 to S907).
- This related content table can be set or updated by manual generation by a system operator or automatic generation based on the state of the system (not shown). For example, in the content stored in a server connected to the network or a storage device connected to the operation terminal, any content that the similar viewer identified in step S905 has viewed in the past. It is possible to create a related content table by extracting from.
- the recommended content processing means 151 has the highest interest / interest level of similar viewers for the content a, or an element of the viewing tendency extraordinary factor (the average per unit time of the interest level in the time interval). The largest element of (value) is obtained, and similarly, content c is obtained, and the content having the highest interest / interest level or viewing tendency vector element value is specified as the recommended content. Also, for example, a content list is generated in descending order of interest and interest level, in descending order, or in a viewing tendency vector, and specified as recommended content.
- Such a viewing tendency correlation calculation method is applied not only when the content is a moving image but also when the content is a web page, a still image, or the like.
- FIG. 11 is a diagram showing screen transition in the recommended content presentation processing.
- viewer 1 When viewer 1 is viewing content on display 11 (A), if search operation is performed using input device 12, recommended content that matches viewer 1's viewing tendency is presented (B). .
- viewer 1 pays attention to the content he wants to see, the screen switches to that content (C).
- Such a series of processing is realized by the viewing tendency management server 100.
- the taste 'interest level calculator 130 calculates the temporal variation of interest' interest level from the physiological response information etc. of the viewer who is watching the content, and the viewing trend analyzer 140 calculates the viewing trend threshold and recommends it
- the content processing means 151 identifies similar viewers from the viewing tendency vector, identifies recommended content from the related content, and presents it to the viewing viewer as useful preference information. This allows viewers to obtain content that suits their own preferences that they have not viewed. That is, it is possible to obtain useful information that suits one's preference without performing complicated operations such as data input and key operations.
- FIG. 12 is a flowchart showing target object information presentation processing.
- a viewer's interest / interest level for an object displayed in a program is calculated, and information (information such as sales sites and services) about the object is presented.
- information information such as sales sites and services
- the viewer 1 is viewing the content ⁇ presented from the presented content database 106.
- the above-mentioned (2) physiological response information / viewer response accumulation processing and (3) viewing tendency analysis processing are performed on the viewer 1 who is viewing the content ⁇ ! (Step S 1 201). That is, the viewing tendency analysis unit 140 calculates a viewing tendency vector for the content ⁇ that the viewer 1 is viewing.
- the object-of-interest information processing means 152 of the information processing unit 150 uses the interest tendency information from the viewing trend vector.
- a region of high interest is identified (step S1202). For example, the region with the highest interest level is specified for the viewing tendency vector composed of the elements of interest / interest level for each region shown in Equation (10).
- the object displayed in the area is specified by a preset table (table in which the area in the content is associated with the object) (step S 1203), and information related to the specified object is determined. Is extracted from an object information data table (not shown), and information about products, services, sales sites, etc.
- Step S 1204 when the viewer 1 has finished viewing the content ⁇ , the attention object information processing means 152 The end of the search mode may be determined in accordance with the operation of the input device 12 by the viewer 1, and information on the object, information on the sales site, etc. may be displayed on the display 11 or transmitted by e-mail.
- FIG. 13 is a diagram showing screen transition in the attention object information presentation processing.
- the object of interest information that matches viewer 1's viewing trend is presented (B).
- the viewer switches to the detailed information screen for the object item (C).
- the object-of-interest information processing means 152 displays information related to the object that is viewed by the viewer 1 on the same screen of the viewing target content shown in FIG. You may make it show.
- control information for processing instructions necessary for product purchase such as placing a product in a virtual shopping cart is transmitted to an external system.
- the interest / interest level calculation unit 130 calculates the interest / interest level for each region on the screen from the physiological response information or the like by the attention object presentation process.
- the viewing tendency analysis unit 140 calculates a viewing tendency vector, and the attention object information processing means 152 identifies an object in a region of high interest / interest level and presents information on the object.
- the viewer can obtain useful information without performing complicated operations such as data input and key operations when obtaining information related to the outside of the object displayed as content.
- FIG. 14 is a flowchart showing viewing tendency influence degree information presentation processing.
- FIG. 15 is a diagram for explaining this process.
- the interest of the later scene Interest in previous scenes' It is known to be affected by interest.
- the degree of influence of the viewing tendency of the immediately preceding scene on the subsequent scene is calculated and presented as viewing tendency influence degree information.
- the viewing tendency influence degree is calculated when the sequence A of the video is presented in the order of scene A ⁇ scene 1 and the sequence B is presented in the order of scene B ⁇ scene 1.
- Interest per unit time of scene A and scene 1 in sequence A 'Interest level is qA, 0, qA, 1 and interest per unit time in scene B and scene 1 in sequence B.
- Interest level is qB, 0, Let qB, 1 be the interest in scene 1 alone.
- the viewing tendency analysis unit 140 calculates the interest level of interest in the scene A in the sequence A and the interest level in the scene 1 from the interest 'interest level calculation unit 130 or the database 103 such as the personal attribute / viewing trend database 103. Enter the interest / interest of scene B in B and the interest / interest of scene 1 as the interest / interest of single scene 1. It is assumed that the personal attribute 'viewing tendency etc. database 103 stores such information in advance. Then, the viewing tendency analysis unit 140 calculates the interest / interest level qA, 0, qA, 1, qB, 0, qB, 1, qO, 1 per unit time according to the above-described equations (3) and (4). Each is calculated (step S1401).
- the interest of the scene 1 portion in the sequence A can be expressed as follows.
- the viewing tendency influence degree processing means 153 of the information processing unit 150 inputs each interest 'interest level calculated by the viewing tendency analysis unit 140, and uses the above-described equations (13) and (14), The viewing tendency influence degree k (qA, 0) that scene A gives to scene 1 and the viewing tendency influence degree k (qB, 0) that scene B gives to scene 1 are calculated (step S 1402).
- the viewing tendency influence degree calculated in this way is provided to, for example, a content provider.
- the viewing tendency influence degree information presentation process allows viewing with sufficient time intervals in the three sequences shown in FIG.
- the mentality calculation unit 130 calculates the temporal variation of interest / interest level
- the viewing tendency analysis unit 140 calculates interest / interest level per unit time in each scene
- the viewing tendency influence degree processing means 15 3 force scene
- the viewing tendency influence level that A gives to scene 1 and the viewing tendency influence degree that scene B gives to scene 1 are calculated.
- Power S can be. For example, the power of the viewing tendency influence that scene A has on scene 1 is higher than the viewing tendency influence that scene B has on scene 1! / If scene B is more interested in scene 1 than scene B It turns out that the interest raising effect is great. This enables content providers to obtain useful information when evaluating content.
- FIG. 16 is a block diagram showing the overall configuration of the viewing tendency management system for explaining the presented content switching processing.
- Fig. 17 is a diagram showing the transition of interest and interest level for explaining the presented content switching process.
- FIG. 18 is a flowchart showing the presented content switching process.
- FIG. 19 is a diagram for explaining the presented content determination process in the flowchart shown in FIG. Figure 16
- the viewing tendency management system 200 for explaining the presented content switching processing is the same as the viewing tendency management system 2 shown in FIG. ⁇ 10- n, display 11 1;! ⁇ 11 1 !!, input device 12-;! ⁇ 12 n, physiological response measuring device 13-;! ⁇ 13 n and IR light 14-;! ⁇ 14-n It is prepared for.
- This processing is performed in the viewing tendency management system 200 of FIG. 16 when a plurality of viewers 1- ;! to 1-n are viewing / listening to the same content. Based on the viewing tendency of n, the content to be presented is determined and presented. Now, it is assumed that the viewers 1-1 to 1-n watch the content presented from the presented content database 106! /.
- a setting unit (not shown in FIG. 2) sets a target audience (step S 1801).
- the setting unit sets the time interval for analyzing the viewing tendency from the past time intervals (0 to j) (step S1802), and selects “entire screen”, “area”, “object” as the analysis target. "Is set (step S 1803). For example, in the content of a video or web page, if the subject of analysis is “entire screen”, it is a sports program, drama, news, CM (commercial), etc. If it is “area”, the person in the screen, The area includes articles, products, news objects, CM objects, etc.
- the “object” is an area including objects such as persons, articles, products, news objects, CM objects in the screen.
- objects such as persons, articles, products, news objects, CM objects in the screen.
- Setting “Area” specify any area from the entire screen by specifying coordinates.
- object is set, the area of the object to be analyzed is set by specifying coordinates.
- the viewing tendency analysis unit 140 reads the interest / interest level and the viewpoint position from the personal attribute / viewing tendency database 103, Alternatively, the interest 'interest level' and the viewpoint position are input from the interest 'interest level calculation unit 130 (step S1804), and the preset viewer;!;! For each “area” and “object”, the interest and interest levels I (t), I (t),..., I (t) are set for the time that the viewpoint stayed in the analysis target.
- the perspective is that
- viewing tendency analysis department 140 calculates, for each analysis target of the viewer 11 1 n, a viewing tendency vector in a preset time interval, that is, an average value per unit time of the interest level in the time interval (step S1805). Since the method for calculating the viewing tendency vector has been described above, a description thereof is omitted here.
- the viewing tendency analysis unit 140 personalizes the interest level I (t), I (t),..., I (t) and the viewing tendency vector of each viewer 1 1 n
- Attribute ⁇ Stored in the viewing tendency database 103.
- the viewing trend analysis unit 140 performs the viewing trend vector ( Interest ⁇ Average value of interest level per unit time as an element for each time interval).
- the presented content switching processing means 154 of the information processing unit 150 is an average value of the interest level that is an element of the threshold value preset by the setting unit and the viewing tendency vector calculated by the viewing tendency analysis unit 140. And the number of viewers who have an average value of interest level exceeding the threshold is counted (step S1806). For example, the number of viewers is counted even if the interest / interest level in one of the preset time intervals exceeds the threshold.
- the presented content switching processing means 154 calculates a ratio from the viewer count and a threshold value preset by a setting unit (not shown in FIG. 2), and the ratio value is preset by the setting unit. If the viewer exceeds the threshold, the viewer determines that he / she is interested in the analysis target, and the content set in advance corresponding to the analysis target by the setting unit in the time interval j + 1 to be presented The display content is determined (step S 1807).
- the setting unit performs analysis "object” and content A, analysis target "area” and content B, analysis target “whole screen” and content C, and other cases. It is assumed that content D has a corresponding! /, And is set! /.
- the presentation content switching processing means 154 presents any content in the content AD when the viewer count exceeds the threshold for each analysis target. Decide as a number. In order to determine any one of a plurality of contents, a preset priority order is used. For example, when only the viewer count of “object” exceeds the threshold, content A is determined as the presented content.
- content presentation ⁇ physiological reaction ⁇ viewer response measuring device 10-l ⁇ 10 -n, display 1 1 1;! ⁇ 11—n, input device 12 — ;! ⁇ 12—n, physiological response measuring device 13 — !! ⁇ 13n and IR light 14 — ;! ⁇ 14n can be configured to share all or part of it.
- the viewing tendency analysis unit 140 causes the viewer's analysis target (“whole screen”, “area”, “ The interest / interest level is set for each object), the viewing tendency vector is calculated for each time interval, and the presentation content switching processing means 154 counts the number of viewers with high interest / interest level for each analysis target. The presentation content is determined based on the viewer count. This allows viewers to switch to highly interested content without performing complicated operations such as data entry and key operations among a plurality of preset viewers.
- FIG. 20 is a flowchart showing attention level determination processing.
- the interest / interest level of the viewer and the viewing tendency vector for the object displayed in the program are calculated, and the attention level information for the object is presented.
- the setting unit (not shown in FIG. 2) Then, the “whole screen”, “area”, “object” and its time zone (time interval) are preset (step S2001).
- the analysis target is as described above.
- the viewing tendency analysis unit 140 reads the interest / interest level and the viewpoint position from the personal attribute / viewing trend database 103 or inputs the interest “interest” and the viewpoint position from the interest “interest level calculation unit 130”. For each set analysis target “entire screen”, “area”, and “object”, set the interest / interest level for the analysis time period in which the viewpoint stayed in the analysis target. The interest / degree of interest is 0 when the viewpoint is not retained in the analysis target. Then, the viewing tendency analysis unit 140 calculates, for each analysis target, a viewing tendency vector in a preset analysis time period, that is, an average value per unit time of interest level in that time period (step S2002). ). Since the method for calculating the viewing tendency vector has been described above, a description thereof is omitted here.
- the attention level determination processing means 155 of the information processing unit 150 views the presence / absence of a viewer response to a mouse click or button press in a preset analysis time period from the physiological response / viewer response database 101.
- the person response is read and determined (step S2003).
- the attention level determination processing means 155 has a high level of attention for the analysis time zone for each analysis target when the following three conditions or at least one condition is satisfied. If none of the conditions are satisfied, it is determined that the degree of attention is low, and is presented as presentation information (step S2004).
- the viewpoint exists within the analysis target area. In the case of interest / interest level power 3 ⁇ 4 in the analysis time zone, the viewpoint does not exist in the analysis target area.
- attention level determination processing a plurality of objects (regions including objects) and time zones are set in advance for content having a video sequence, and whether or not the viewer pays attention to each object. , Calculate the ratio (attention rate) of the objects that noticed out of the set objects, and respond to the objects that were determined to be noticed Time (reaction time) is calculated, and these pieces of information are output as presentation information.
- an object may be analyzed, and a plurality of objects may be set in advance, and the entire force screen that is processed for each object may be processed as an analysis target.
- a plurality of regions may be set in advance with a region having an arbitrary shape as an analysis target, and processing may be performed for each region.
- the shape of the set area is saved as bitmap information (the analysis target part is saved as 1 and the others are saved as 0). If the bitmap information at the viewpoint position is 1, it is within that area. If it is 0, it is determined that it is not in that area.
- FIG. 21 is a diagram showing the transition of the interest level for explaining the attention level determination process.
- FIG. 22 is a diagram illustrating an object for explaining the attention level determination process.
- the setting unit sets the time interval j ⁇ 1 [ ⁇ , ⁇ ] where the object A is presented as the time zone of the interest level determination interval on the time axis indicating the transition of the interest level of interest shown in FIG. here
- T is the start time of time interval j 1 and T is the end time.
- the area including the object A shown in FIG. 22 is set.
- the area including object A is
- the attention level determination processing means 155 performs the time interval j ⁇ 1 (time interval [ ⁇ , T
- Viewing tendency database 103 stores interest, interest level (see Fig. 21), viewpoint position and synchronization information for a certain content, and physiological response / viewer response database 101 stores Viewer responses such as mouse clicks and button presses on the content and synchronization information are stored.
- the viewing tendency analysis unit 140 reads the interest / interest level, the viewpoint position, and the synchronization information from the personal attribute / viewing tendency database 103, and at the time t (T ⁇ t ⁇ T) based on the synchronization information.
- Viewpoint viewpoint position
- the time interval when it is determined that the viewpoint is in the area including the object A is T ⁇ t ⁇
- the viewing tendency analysis unit 140 calculates an average value per unit time for the interest / interest level in the viewpoint coincidence section.
- the viewing tendency analysis unit 140 stores the average value per unit time of interest / interest in the viewpoint coincidence section in the personal attribute / viewing tendency database 103 together with the synchronization information and the information on the viewpoint coincidence section.
- the degree-of-attention determination processing means 155 of the information processing unit 150 inputs an average value per unit time of interest / interesting degree in the viewpoint coincidence section from the viewing tendency analysis unit 140 or the personal attribute / viewing tendency database 103. , Physiological reaction ⁇ Viewer response database 101 Input viewer response and synchronization information. Then, the attention level determination processing means 155 determines whether or not the viewer response is received in the viewpoint coincidence interval based on the synchronization information. If it is determined that there is a viewer response within the viewpoint coincidence time period, the interest- Whether the average value q of the heart rate per unit time exceeds a preset threshold th
- the viewing tendency analysis unit 140 calculates the integral value Q of the interest / interest level in the time point coincidence section, and the attention degree determination processing means 155 is calculated by the viewing tendency analysis unit 140.
- the attention level determination processing unit 155 determines whether or not attention has been paid to a plurality of preset objects in a preset time zone. For example, in Fig. 21, if the time zone for object B is set to time interval j, the time zone for object C is set to time interval j + 2, and the time zone for object D is set to time interval j + 4, the degree of attention The determination processing means 155 determines whether or not attention is paid to each object.
- the attention level determination processing means 155 calculates the attention rate R by the following equation.
- N indicates the number of objects set in advance
- n indicates the number of objects determined to be focused.
- the attention level determination processing means 155 determines the response time when it is determined that attention has been paid (Reaction time) is calculated.
- Reaction time the response time S for object A can be expressed as
- T is the viewer response time (eg, button press time) and ⁇ is the time interval
- the response time refers to the time from the start time when the attention degree determination process for object A is performed (after object A shown in FIG. 22 is presented (displayed on the screen)) to the button press time by the viewer. .
- the attention level determination processing means 155 calculates the average value, variance, etc. of the response time, and uses these information to determine the tendency of the viewer's response response Information is provided to content providers.
- the interest / interest degree calculator 130 calculates the interest and the degree of interest, and the viewing tendency analyzer Calculate the integrated value or the average value per unit time for the interest / interest level in the point of view coincidence in the analysis time zone where 140 is preset. Then, the attention level determination processing means 155 determines whether or not the object A has been noticed for each of a plurality of viewers. Further, the attention degree determination processing unit 155 pays attention to the object A by dividing the number of viewers determined to have paid attention to the object A by! /, The number of viewers set in advance. Calculate the percentage of viewers who were engaged.
- the viewpoint of the viewer who was paying attention to object A is in the area including object A (area to be analyzed)! /, And the time length is calculated, paying attention to object A! /, The average value, variance value, standard deviation value, and maximum value for all viewers who were paying attention to object A from the integrated value of interest / interest level or the average value per unit time during the viewpoint coincidence period And the minimum value is calculated.
- the attention level determination processing unit 155 performs the interest level determination process for a predetermined analysis target (a plurality of objects) and a time zone. Based on the integrated value of the degree of interest or the average value per unit time, it is determined whether or not the viewer is paying attention to each object, the attention rate is calculated, and further, the object determined to be paying attention is calculated. ! /, And the response time (reaction time) was calculated, and this information was presented as attention degree information. As a result, content providers, etc. It is possible to obtain attention level information as useful information for content evaluation without performing complicated operations such as data entry and key operations in the specified analysis target and time zone.
- the attention level determination processing means 155 determines viewers who have focused attention on the object to be analyzed among a plurality of preset viewers, and the ratio, the length of time for which the analysis target has been viewed, etc. Statistical information was calculated. These statistical information can be used to judge the effectiveness of the specified area of the content. Thereby, the content provider can obtain useful information for content evaluation.
- the attention level determination process uses, for example, content that captures a scene where a human operates a machine! /, Or content that captures a scene imitating the operation.
- content that captures a scene imitating the operation it is possible to educate viewers on how to operate the machine and safety.
- the viewer receiving the education is provided with a monitor that displays the operation status of the facility, an operation status lamp, an alarm lamp, etc. View the content that captured the status of the control panel.
- the attention level determination processing means 155 determines whether or not each of a plurality of preset analysis targets (for example, an area including an alarm lamp) and a time zone pay attention to! And the response time is calculated.
- the attention level determination processing means 155 determines whether or not the viewer has focused on the lighting of the alarm lamp, and after performing a predetermined operation (viewer response Response time until) is calculated.
- the attention level determination processing means 155 presets information related to necessary operations on the analysis target (operation information) and a threshold for the response time of the analysis target, and based on the viewer response and the above-described operation information. If the viewer response matches the operation information, it is determined that the correct operation has been performed, and if it does not match, it is determined that the correct operation has not been performed.
- the attention level determination processing means 155 determines that the operation timing is appropriate when the response time is within the threshold based on the response time and the above-described threshold, and when the response time is not within the threshold, Judge that the timing was not appropriate. Also, the attention level determination processing means 155 determines whether or not an effective operation has been performed within an appropriate time when the warning lamp is lit by these determinations, and includes the determination result. Present as information. Further, the attention degree determination processing means 155 Then, the above-described processing is performed for a plurality of analysis objects, and the ratio is calculated by dividing the number of analysis objects for which effective operations are performed within an appropriate time by the total number of analysis objects, and the ratio of the viewer is calculated based on the ratio.
- the proficiency level is calculated (for example, the calculated ratio is regarded as the proficiency level) and presented as attention level information. Accordingly, the viewer can determine the analysis target that should be focused in spite of the attention and the level of proficiency of the viewer based on the presented attention level information. In this way, by using content that captured machine operations, the ability of viewers to become proficient in machine operations, the power that should be focused on, and the safe operation Therefore, it is possible to use the viewing tendency management server 100 that performs such attention degree determination processing as a tool for machine operation education. it can.
- FIG. 23 is a flowchart showing the favorable / disgusting determination process.
- the viewer's preference or dislike sensitivity for the object displayed in the program is calculated and the information is presented.
- the setting unit (not shown in FIG. 2) presets a region including the “object” to be analyzed and its time zone (step S2301).
- the viewing tendency analysis unit 140 reads the interest, the interest level, and the viewpoint position from the personal attribute / viewing tendency database 103, or inputs the interest “interesting” interest level and the viewpoint position from the interest “interest level calculation unit 130” and analyzes them.
- set the interest / interest level of the viewpoint coincidence section indicating the time when the viewpoint stays in the area including the preset “object” to be analyzed!
- the interest / interest level when the viewpoint does not stay in the area is 0.
- the viewing tendency analysis unit 140 calculates a time (interest / interest duration) that satisfies a predetermined condition from the interest level of interest in the interval of viewpoint coincidence (step S2302), and uses the interest / interest duration as viewing trend information.
- the time satisfying the predetermined condition means the time from the point in time when the interest-interest level becomes equal to or higher than a preset threshold to the point in time when the viewpoint deviates from the area.
- the interest / interest level is expected during the time that satisfies the predetermined condition. It can also be the time between the time when the threshold is set higher than the preset threshold and the time when the interest / interest level falls below the preset threshold.
- the likability / disgust determination processing means 156 of the information processing unit 150 inputs the viewing tendency information of interest / interest duration in the area including the “object” to be analyzed from the viewing tendency analysis unit 140, Compared with the set threshold value, a favorable feeling and a disgusting feeling are determined (step S2303). Similarly, likability and disgust are determined for a plurality of areas in which the same “object” is analyzed. Favorability is calculated based on the total number of analysis targets and the number of analysis target areas determined to be favorable, and the total number of analysis target areas and analysis target areas determined to be disgusting are calculated. Based on the number, the aversion sensitivity is calculated and the information is output as presentation information (step S2304).
- this likability / dislikeness determination process is to set the object (area including the object) and the time zone to be analyzed in advance for the content having a video sequence, and the viewer can set the object for the set object. It is determined whether the person has a good feeling! /, Or a bad feeling! /, And the goodness is calculated from the number of objects (number of areas) that has been determined to have a good feeling. Disgust is calculated from the determined number of objects (number of areas), and this information is output as presentation information.
- a setting unit (not shown) in FIG. 2 presets a region including the “object” to be analyzed and its time zone. For example, when the object / object A is presented on the time axis indicating the transition of interest and interest shown in Fig. 21! /, The time interval] 1 [ ⁇ , T] is the target of analysis
- T is the start time of time interval j-1 and T is the end time
- time interval j1 Indicates the time.
- object A is presented over the entire time, but it may not necessarily be presented over the entire time, and there may be times when it is presented multiple times. Also good.
- the setting unit sets an area including the object A shown in FIG. Here, the area containing object A is
- X ⁇ AR (t) A rectangular area specified by ( ⁇ ( ⁇ ), AR (t)).
- the favorable / disgusting judgment processing means 156 determines the time interval of content j ⁇ l [T, ⁇ ]
- likability is calculated based on the number of object A (number of regions) determined to be favorable, and the number of object A determined to be disgusting ( The aversion sensitivity is output as presentation information based on the number of areas).
- the personal attribute / viewing tendency database 103 stores interest 'interest level (for example, see Fig. 21), viewpoint position, and synchronization information for a certain content.
- the viewing tendency analysis unit 140 reads the interest / interest level, viewpoint position, and synchronization information from the personal attribute / viewing trend database 103, and uses the synchronization information at time t (T ⁇ t ⁇ T).
- Viewpoint viewpoint position
- E ⁇ t) ⁇ (E x (t), E y (t)) is within the region including the object A is determined by the following expression.
- the viewpoint coincidence interval determined that the viewpoint is in the area including the object A is T
- viewing tendency analysis section 140 determines whether interest / interest level I (t) in the point-of-view coincidence interval is greater than or equal to threshold th by an expression of I (t) ⁇ th. And T is used as a reference
- the time t at which the interest / interest degree I (t) is first determined to be equal to or greater than the threshold th is identified. So
- Interest in interest and interest duration ⁇ is calculated by the following formula.
- the interest / interest duration T in the area including object A is used as viewing tendency information.
- the interest / interest duration T in the area including object A is
- the setting unit (not shown in FIG. 2) may set the entire force screen in which one place in the rectangular area in the screen is set as the “object” to be analyzed.
- An area having an arbitrary shape may be set.
- an area including a plurality of objects other than one object may be set.
- the setting unit stores the shape of the set region as bitmap information (the target region is stored as 1 and the others are stored as 0), and the viewing direction analysis unit 140 stores the bitmap information of the viewpoint position. If it is 1, it is determined that it is in that area, and if it is 0, it is determined that it is not in that area.
- Favorable / disgusting judgment processing means 156 of the information processing unit 150 inputs the interest in the region including the object A from the viewing tendency analysis unit 140 or the personal attribute 'viewing tendency database 103; ⁇ Interest duration T and preset object
- the setting unit sets a plurality of areas for the same object A on the screen, and the favorable / disgust determination processing means 156 determines the positive and negative feelings of the object A for each area. To do.
- the favorable feeling / disgusting judgment processing means 156 is set as an analysis target. N is the total number of areas, n is the number of areas determined to be favorable, and g is determined to be disgusting g
- the favorable sensitivity Pg and the aversion sensitivity Pb are calculated by the following formulas, and these b
- the information is presented to the content provider, etc. as information for judging the degree of likability and dislike of object A! /.
- 100 is multiplied to display the percentage.
- FIG. 27 shows the interest / interest level data collected by the experiment.
- the vertical axis represents the region of interest to the viewer 1 (where the viewpoint position exists) and the interest-interest level
- the horizontal axis represents the elapsed time.
- the solid line indicates the area that is viewed by viewer 1
- the dotted line indicates the interest level.
- different objects that cause disgust are presented in the areas A to D
- different objects that cause positive feelings are presented in the areas A ′ to D ′.
- Fig. 27 (1) viewer 1 has four objects that are disgusted: region B-> outside region-> region A-> outside region-> region A-> outside region-> region ⁇ -> ⁇
- the viewpoint moves in the order of power. It can also be seen that the degree of interest at that time gradually increases, but tends to decrease without staying in the attention area for a long time, or to divert the viewpoint from the attention area.
- the interest / interest continuation time is less than or equal to the disgust threshold, that is, if the viewer's 1 emotion on the object is a certain force S, and the gaze is diverted in a short time, the object has disgust. Can be determined.
- viewer 1 determines the region for the four objects that are favorable. It can be seen that the viewpoint moves in the order of area A ′ ⁇ outside area ⁇ area B ′ ⁇ outside area ⁇ area B ′ ⁇ outside area ⁇ area B ′ ⁇ . It also shows that the interest and interest level at that time gradually increases and tends to be maintained for a long time. In other words, if the interest / interest continuation time is greater than or equal to the favorable threshold, that is, if the viewer 1 is interested in the object and does not look away, Can be judged.
- the likability-aversion determination processing unit 156 performs the likability-aversion determination processing unit 156 according to the preset object to be analyzed and the time zone. Judgment of likability and disgust is calculated, likability is calculated based on the number of areas including objects determined as likable, and aversion sensitivity is calculated based on the number of areas including objects determined as hateful. This information was presented. As a result, content providers can obtain positive and negative information as useful information for evaluating objects to be analyzed without complicated operations such as data entry and key operations. Become.
- FIG. 24 is a flowchart showing the impression evaluation process.
- the degree of impression is calculated by combining the viewer's likability or aversion to the object displayed during the program, and this information is presented.
- step S2401 of the impression evaluation process to step S2404 is the same as the process from step S2301 to step S2304 of the favorable / disgust determination process shown in FIG. The description is omitted here.
- the impression evaluation processing means 157 of the information processing unit 150 calculates an impression degree based on the favorable sensitivity and the disgusting sensitivity, and outputs this information as presentation information (step S2405). Specifically, if the total number of areas set as analysis targets is N, the number of areas determined to be favorable is n, and the number of areas determined to be disgust is n, the impression
- the impression evaluation processing means 157 includes the number n of areas determined to be favorable and n
- the degree may be calculated. Further, the impression evaluation processing means 157 is set so that the analysis target set by the setting unit is the entire screen, and the analysis time period is a few seconds (for example, 5 to 6 seconds) from when the screen is viewed. The impression degree may be calculated for the analysis target and the analysis time zone. As a result, the impression corresponding to the emotional reaction can be evaluated, and the impression that the entire screen gives to the viewer 1 in a short time can be improved.
- the impression evaluation processing means 157 gives a good feeling and a bad feeling for the preset object to be analyzed and the time zone by the impression evaluation process.
- the degree of impression was calculated based on the number of areas that included the objects that were determined to be favorable and the objects that were determined to be disgusted, and this information was presented.
- the content provider can obtain impression information as useful information for evaluation on the object to be analyzed without performing complicated operations such as data input and key operations.
- FIG. 25 is a flowchart showing the designated area emotional effect processing.
- this processing calculates the emotional level that indicates the degree of temporary emotion that is rapidly caused for an object displayed during the program based on the favorable and disgusting sensitivity to the object and the final operation of viewer 1. This information is presented.
- the setting unit presets the area including the “object” to be analyzed, its time zone, and the final operation target area (step S2501).
- the final operation target area is the final operation (for example, by pressing a button, a mouse operation, or blinking) as a response response by the viewer 1 to the object. This is an area for inputting an instruction operation or the like.
- the viewing tendency analysis unit 140 determines, based on the interest-interest level in the point-of-view matching interval, for the region including the “object” to be analyzed. Interest / interest duration is calculated (step S2502).
- the designated area emotional effect processing means 158 of the information processing unit 150 reads the final operation information in the final operation target area, which is the viewer response information b, from the physiological response / viewer response database, and determines whether or not there is a final operation. Is determined (step S2503). Then, the designated area emotional effect processing means 158 determines the favorable feeling by comparing the interest / interest duration and the preset threshold value in the same manner as in step S2303 and step S2304 in FIG. 23, and calculates the favorable feeling. (Step S2504, Step S2505).
- the designated area emotional effect processing means 158 indicates that the number of all areas set as the analysis target is N, the number of areas determined to be favorable is n, and the presence or absence of the final operation is G (final operation).
- the specified area emotional effect M is calculated by the following formula, and this information is rapidly applied to the object. It is presented to the content provider, etc., as information for determining the degree of temporary emotion that is caused (step S2506). In the following formula, 100 is multiplied to display the percentage.
- the designated area emotional effect processing means 158 determines a favorable feeling for the preset object to be analyzed and the time zone by the designated area emotional effect process. Based on the number of areas including objects judged to be favorable and the presence / absence of viewer 1's final operation, the designated area emotional level was calculated and this information was presented. As a result, the content provider or the like, for example, browses the product expected by the viewer 1 on the web page and shows whether or not the final operation such as purchasing the product as a result of showing the interest is shown. Can be determined. In addition, as useful information for evaluating objects that do not require complicated operations such as data entry and key operations, it is possible to obtain information on the temporary emotional degree V that is rapidly caused to objects. Become.
- the display 11 may be a screen screen panel or a liquid crystal display panel of a projector in addition to a normal cathode ray tube receiver.
- the camera provided in the physiological reaction measuring device 13 is preferably an infrared camera using the IR light 14, but is not limited thereto. In the case of an infrared camera, it is possible to obtain a high-contrast image that excludes external images reflected in the iris, and is effective in that image processing and data analysis can be performed stably and at high speed.
- the physiological reaction measuring device 13 when inputting physiological response information from the viewer 1, for example, a stand for imaging the eyeball of the viewer 1 at a position 50 to 100 cm away from the viewer 1 is used.
- the physiological reaction measuring device 13 is set. In this case, a chin rest may be used to fix the position of the viewer's 1 head.
- the physiological reaction measuring device 13 It is also possible to obtain eye movement physiological response information with high accuracy by automatically tracking the position of the face and the position of the eyeball.
- the camera may be attached to the head of the viewer 1 using a head-mounted device.
- a general scene that can be visually recognized by the viewer 1 may be used instead of using the video content previously captured as a viewing target.
- a separate camera that is mounted in the opposite direction to the camera of the physiological response measuring device 13 is simultaneously photographed for the scene within the viewing angle of the viewer 1, and the photographed video is presented as the presented video content. You may make it process as an equivalent.
- the hardware of the content presentation / physiological reaction / viewer response measuring device 10, the viewing inclination management server 100, and the content distribution server 105 is of the personal computer (personal computer) class. Also good.
- the content presentation / physiological reaction / listener response measuring device 10 may be a desktop computer equipped with a large display 11 or a portable information terminal such as a mobile phone equipped with a camera. Good.
- the input device 12 may be a button, keyboard, touch panel panel, remote control, or controller attached to a game device, and a viewer response is generated as time series data by the operation of the viewer 1. Anything is acceptable.
- the physiological response / viewer response database 101, the reference content database 102, and the personal attribute / viewing tendency database 103 are connected to the viewing tendency management server 100 via the network 104. May be.
- the content distributed by the content distribution server 105 has a format including at least one of video data, web page data, computer game data, and computer program output data.
- the display 11 displays at least one of a character string, a figure, a symbol, a picture, a photograph, and a video, and information for making the viewer 1 respond.
- the content read-out display unit 110 performs reference content (for example, content in which a full-screen black and white screen becomes a still image for about several seconds). Is appropriately presented to the viewer 1 so that the interest level and the interest tendency vector are corrected based on the physiological response information and the viewer response. May be.
- the interest / interest level calculator 130 calculates the maximum value Pmax and the minimum value Pmin of the pupil diameter in the black screen scene and the white screen scene, respectively, and uses these values for calculating the interest level (interest level) ( (See equations (1) and (2)). This makes it possible to calculate the degree of interest / interest that absorbs individual differences in pupil dilation and dilation. Therefore, the viewing tendency vector can be normalized, and the accuracy of the processing of viewing tendency information can be improved.
- the viewing tendency management server 100 is configured by a computer including a volatile storage medium such as a CPU and RAM, a nonvolatile storage medium such as a ROM, an interface, and the like.
- a volatile storage medium such as a CPU and RAM
- a nonvolatile storage medium such as a ROM, an interface, and the like.
- the functions of the content reading and presentation unit 110, the information capture unit 120, the interest 'interest level calculation unit 130, the viewing tendency analysis unit 140, and the information processing unit 150 provided in the viewing trend management server 100 describe these functions. Each is realized by causing the CPU to execute the program.
- These programs are stored in a storage medium such as a magnetic disk (floppy disk, hard disk, etc.), optical disk (CD-ROM, DVD, etc.), semiconductor memory, and distributed.
Landscapes
- Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Theoretical Computer Science (AREA)
- Databases & Information Systems (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- Signal Processing (AREA)
- General Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Physiology (AREA)
- Health & Medical Sciences (AREA)
- Biomedical Technology (AREA)
- Biophysics (AREA)
- General Health & Medical Sciences (AREA)
- Molecular Biology (AREA)
- Life Sciences & Earth Sciences (AREA)
- Computing Systems (AREA)
- Human Computer Interaction (AREA)
- Two-Way Televisions, Distribution Of Moving Picture Or The Like (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
Description
Claims
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Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH09114846A (ja) * | 1995-10-16 | 1997-05-02 | Fujitsu Ltd | ブラウジング表示方法および画像表示システム |
JP2002092023A (ja) * | 2000-09-14 | 2002-03-29 | Nippon Telegr & Teleph Corp <Ntt> | 情報提供装置および方法と情報提供プログラムを記録した記録媒体 |
JP2002183212A (ja) * | 2000-12-19 | 2002-06-28 | Fuji Xerox Co Ltd | 電子文書加工システム、電子文書加工方法、及び、コンピュータ読取り可能な記録媒体 |
JP2003250146A (ja) * | 2001-12-21 | 2003-09-05 | Nippon Telegr & Teleph Corp <Ntt> | 番組選択支援情報提供サービスシステムとサーバ装置および端末装置ならびに番組選択支援情報提供方法とプログラムおよび記録媒体 |
JP2005182603A (ja) * | 2003-12-22 | 2005-07-07 | Fuji Xerox Co Ltd | 情報処理装置、および情報処理方法、並びにコンピュータ・プログラム |
-
2007
- 2007-12-14 JP JP2008549381A patent/JP4865811B2/ja not_active Expired - Fee Related
- 2007-12-14 WO PCT/JP2007/074156 patent/WO2008072739A1/ja active Application Filing
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH09114846A (ja) * | 1995-10-16 | 1997-05-02 | Fujitsu Ltd | ブラウジング表示方法および画像表示システム |
JP2002092023A (ja) * | 2000-09-14 | 2002-03-29 | Nippon Telegr & Teleph Corp <Ntt> | 情報提供装置および方法と情報提供プログラムを記録した記録媒体 |
JP2002183212A (ja) * | 2000-12-19 | 2002-06-28 | Fuji Xerox Co Ltd | 電子文書加工システム、電子文書加工方法、及び、コンピュータ読取り可能な記録媒体 |
JP2003250146A (ja) * | 2001-12-21 | 2003-09-05 | Nippon Telegr & Teleph Corp <Ntt> | 番組選択支援情報提供サービスシステムとサーバ装置および端末装置ならびに番組選択支援情報提供方法とプログラムおよび記録媒体 |
JP2005182603A (ja) * | 2003-12-22 | 2005-07-07 | Fuji Xerox Co Ltd | 情報処理装置、および情報処理方法、並びにコンピュータ・プログラム |
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JP4865811B2 (ja) | 2012-02-01 |
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