WO2022130822A1 - 画像表示装置、画像表示システム、画像表示方法および非一時的なコンピュータ可読媒体 - Google Patents
画像表示装置、画像表示システム、画像表示方法および非一時的なコンピュータ可読媒体 Download PDFInfo
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Definitions
- the present invention relates to an image display device, an image display system, an image display method, and a non-temporary computer-readable medium.
- Patent Document 1 discloses a system for grasping a change in a user's physical condition.
- the user searches for similar measurement data similar to the latest measurement data among the past measurement data of other users. Estimate illnesses or symptoms that may occur in the near future.
- Patent Document 2 describes a nosocomial infection influence range browsing system.
- This system has a round route device, a round log recording terminal, a log analysis unit, and a map display unit.
- the round route device is installed in the medical facility, and the round log recording terminal records the round information of the person from the communication record with the round route device.
- the log analysis unit analyzes round information based on preset analysis rules and calculates the infection risk of a person.
- the map display unit displays the range of infection influence in the medical facility based on the preset map information, the movement route of the person obtained by the round information, and the infection risk of the person.
- Patent Document 3 discloses a home therapy patient rescue system having a monitor center connected to a medical device used by a home therapy patient through a communication means and a database for storing personal information of the home therapy patient.
- the monitor center detects the condition of the medical device used by the home therapy patient at regular intervals, searches the database in the event of a disaster, and creates a list of relief priorities in order of severity.
- the present disclosure has been made in view of such problems, and an object of the present disclosure is to provide an image display device or the like that preferably displays a situation with a high risk of infection.
- the image display device includes an image data acquisition means, a specific means, an estimation means, a attention image detection means, and an output means.
- the image data acquisition means acquires a plurality of image data from the camera.
- the identification means identifies a person from the image data.
- the estimation means estimates the possibility of developing an infectious disease of a identified person from image data.
- the attention image detecting means detects the attention image including the attention person having the possibility of onset and the peripheral person in the vicinity of the attention person.
- the output means extracts and displays a series of images including the image of interest.
- the computer executes the following method.
- the computer acquires a plurality of image data from the camera.
- the computer identifies a person from the image data.
- the computer estimates the likelihood of developing an infection in a particular person. Based on the estimation result, the computer detects the attention person having the possibility of developing the disease and the attention image including the peripheral person in the vicinity of the attention person.
- the computer extracts a series of images including the image of interest.
- the program according to one embodiment of the present disclosure causes a computer to perform the following steps.
- the computer acquires a plurality of image data from the camera.
- the computer identifies a person from the image data.
- the computer estimates the likelihood of developing an infection in a particular person. Based on the estimation result, the computer detects the attention person having the possibility of developing the disease and the attention image including the peripheral person in the vicinity of the attention person.
- the computer extracts a series of images including the image of interest.
- an image display device or the like that suitably displays a situation with a high risk of infection.
- FIG. It is a block diagram of the image display device which concerns on Embodiment 1.
- FIG. It is a flowchart which shows the image display method which concerns on Embodiment 1.
- FIG. It is a block diagram of the image display system which concerns on Embodiment 2.
- FIG. It is a figure which shows the example of the image group extracted by the image display apparatus which concerns on Embodiment 2.
- FIG. It is a block diagram of the image display device which concerns on Embodiment 3.
- FIG. It is a block diagram of the image display device which concerns on Embodiment 4.
- FIG. It is a block diagram of the image display device which concerns on Embodiment 5.
- FIG. 1 is a block diagram of the image display device 10 according to the first embodiment.
- the image display device 10 shown in FIG. 1 is connected to a camera installed in a predetermined facility or outdoors, acquires image data taken by the camera, and displays a remarkable image or image group.
- the image display device 10 has an image data acquisition unit 111, a specific unit 112, an estimation unit 113, an attention image detection unit 114, and an output unit 115 as main configurations.
- the image data acquisition unit 111 acquires a plurality of image data from the camera.
- the plurality of image data are image data taken at different times.
- the camera captures 30 frames of images per second and supplies the image data related to these captured images to the image data acquisition unit 111.
- the number of cameras connected to the image data acquisition unit 111 may be one or a plurality.
- the camera to which the image data acquisition unit 111 is connected may be fixed for shooting a predetermined angle of view, or may be a movable one that pans, tilts, or zooms.
- the image data acquisition unit 111 supplies the image data acquired from the camera to at least the specific unit 112. Further, the image data acquisition unit 111 supplies the image data acquired from the camera to other configurations as appropriate.
- the identification unit 112 receives image data from the image data acquisition unit 111, and identifies a person from the received image data. More specifically, for example, the specific unit 112 extracts the feature amount of the received image data and detects the feature amount of the person. The specific unit 112 supplies data (specific data) related to the specified person to the estimation unit 113.
- the estimation unit 113 receives specific data from the specific unit 112, and estimates the possibility of developing an infectious disease of the specified person by using the received specific data. More specifically, for example, the estimation unit 113 receives the state of the body movement of the person as characteristic data, and detects that the specified person shows the symptomatic movement related to the onset of the infectious disease. Symptom movements related to the occurrence of an infectious disease are, for example, coughing, sneezing, touching the buttocks, touching the chest, and the like. The estimation unit 113 estimates whether or not there is a possibility of developing an infectious disease for the specified person. In this case, the estimation unit 113 may presume that the identified person has a possibility of developing an infectious disease when the specified person performs a preset operation.
- the estimation unit 113 may estimate whether or not the possibility of developing an infectious disease is equal to or higher than a preset threshold value from a plurality of actions of the specified person.
- the estimation unit 113 supplies the result of the estimation to the attention image detection unit 114.
- the attention image detection unit 114 includes a person of interest who may have developed an infectious disease from a plurality of image data acquired by the image data acquisition unit 111 by using the estimation result received from the estimation unit 113. Detect the image.
- the "person of interest” refers to a person estimated by the estimation unit 113 to have a possibility of developing an infectious disease.
- the attention image detection unit 114 detects a attention image including a person of interest and a peripheral person from a plurality of image data acquired by the image data acquisition unit 111.
- peripheral person means, for example, a person whose distance to the person of interest is closer than a preset value.
- the definition of peripheral persons is not limited to the above-mentioned contents.
- the peripheral person may be a person whose distance to the person of interest is closer than a preset value and exists for a preset period or longer. That is, a peripheral person is a person who is close to a person of interest who may develop an infectious disease and who may be transmitted an infectious disease from the person of interest.
- the attention image detection unit 114 determines that the situation where the infectious disease may be transmitted from the attention person to the surrounding person is a situation where the infection risk is high, and detects the captured image as the attention image. When the attention image detection unit 114 detects the attention image, the attention image detection unit 114 supplies data related to the attention image to the output unit 115.
- the output unit 115 receives data related to the attention image from the attention image detection unit 114, and extracts a series of image groups including the attention image from the received data.
- the output unit 115 extracts, for example, a group of images for a preset period including the image of interest.
- the preset period is, for example, 5 seconds before and after the image of interest, 10 seconds or 30 seconds, respectively.
- the "image group” is an image taken continuously. Therefore, the "image group” may be referred to as a "moving image”.
- the output unit 115 outputs the extracted image group to a predetermined display device to be connected.
- the image display device 10 may detect a person suspected of developing an infectious disease from the image data acquired from the camera, and may have transmitted the infectious disease to a person in the vicinity of the person. Images can be extracted and displayed.
- FIG. 2 is a flowchart showing the image display method according to the first embodiment.
- the flowchart shown in FIG. 2 is started, for example, by activating the image display device 10.
- the image data acquisition unit 111 acquires a plurality of image data from the camera (step S11).
- the image data acquisition unit 111 supplies a plurality of acquired image data to at least the specific unit 112.
- the identification unit 112 receives image data from the image data acquisition unit 111, and identifies a person from the received image data (step S12).
- the specific unit 112 identifies a person, the specific unit 112 supplies specific data to the estimation unit 113.
- the estimation unit 113 estimates the possibility of developing an infectious disease in the specified person by using the specific data received from the specific unit 112 (step S13).
- the estimation unit 113 supplies the estimation result to the attention image detection unit 114.
- the attention image detection unit 114 detects the attention image including the attention person having a possibility of onset and the peripheral person in the vicinity of the attention person from the estimation result received from the estimation unit 113 (step S14). ..
- the attention image detection unit 114 supplies the detected attention image to the output unit 115.
- the output unit 115 extracts a series of image groups including the attention image from the attention image received from the attention image detection unit 114, and outputs the extracted series of image groups to a predetermined display device (step S15).
- the image display device 10 has a processor and a storage device as a configuration (not shown).
- the storage device included in the image display device 10 includes a storage device including a non-volatile memory such as a flash memory or an SSD (Solid State Drive).
- the storage device included in the image display device 10 stores a computer program (hereinafter, also simply referred to as a program) for executing the above-mentioned image display method.
- the processor reads a computer program from the storage device into a buffer memory such as a DRAM (Dynamic Random Access Memory) and executes the program.
- a buffer memory such as a DRAM (Dynamic Random Access Memory)
- Each configuration of the image display device 10 may be realized by dedicated hardware. Further, a part or all of each component may be realized by a general-purpose or dedicated circuitry, a processor, or a combination thereof. These may be composed of a single chip or may be composed of a plurality of chips connected via a bus. A part or all of each component of each device may be realized by the combination of the circuit or the like and the program described above. Further, as a processor, a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), an FPGA (field-programmable gate array), or the like can be used. It should be noted that the description of the configuration described herein may also be applied to other devices or systems described below in the present disclosure.
- each component of the image display device 10 when a part or all of each component of the image display device 10 is realized by a plurality of information processing devices and circuits, the plurality of information processing devices and circuits may be centrally arranged. It may be distributed.
- the information processing device, the circuit, and the like may be realized as a form in which each is connected via a communication network, such as a client-server system and a cloud computing system.
- the function of the image display device 10 may be provided in the SaaS (Software as a Service) format.
- the embodiment 1 has been described above.
- the image display device 10 according to the first embodiment detects a person of interest showing symptoms of an infectious disease in a place where a plurality of people come and go, and there is a possibility that the infectious disease is transmitted to a person existing in the vicinity of the person of interest. You can display an image that includes a certain situation. Therefore, according to the first embodiment, it is possible to provide an image display device or the like that suitably displays a situation where the risk of infection is high.
- FIG. 3 is a block diagram of the image display device 20 according to the second embodiment.
- the image display device 20 shown in FIG. 3 is different from the first embodiment in that it has a thermal image data acquisition unit 116 and a storage unit 120.
- the thermal image data acquisition unit 116 acquires thermal image data from an infrared camera (or thermal camera).
- the camera connected to the image data acquisition unit 111 is also referred to as a "visible light camera” in order to facilitate the distinction from the infrared camera.
- the image data generated by the visible light camera is also referred to as “visible light image data”.
- the infrared camera is installed corresponding to the visible light camera connected to the image data acquisition unit 111.
- Visible light cameras and infrared cameras are installed in a predetermined facility, in the vicinity of the facility, or in a predetermined place outdoors.
- the visible light camera captures a landscape including a person, generates visible light image data related to the captured landscape image, and supplies the generated visible light image data to the image data acquisition unit 111.
- the infrared camera captures a landscape including a person, generates thermal image data for the captured landscape image, and supplies the generated thermal image data to the thermal image data acquisition unit 116.
- the visible light camera and the infrared camera overlap at least a part of the shooting range.
- the infrared camera has a shooting range corresponding to at least a part of the visible light image taken by the visible light camera.
- the visible light camera and the infrared camera are fixed so that their positional relationship does not change.
- the photographing apparatus can associate the image of the person included in the visible light image data generated by the visible light camera with the image of the person included in the thermal image data generated by the infrared camera.
- the visible light camera and the infrared camera may be one or more. Further, for example, the visible light camera or the infrared camera may be movable so that the positional relationship with each other changes. In this case, the visible light camera or the infrared camera may temporarily pan, tilt, or zoom by the user's operation, for example, and even if the angle of view is changed, it may automatically return to the predetermined position. preferable.
- the thermal image data acquisition unit 116 acquires thermal image data from the above-mentioned infrared camera, and supplies the acquired thermal image data to the estimation unit 113.
- the estimation unit 113 in the present embodiment measures the body surface temperature of a person included in the thermal image data. For example, the estimation unit 113 first extracts a person's image from the visible light image data. At this time, the estimation unit 113 may extract only a specific part such as a face image in the body of the person. Next, the estimation unit 113 extracts thermal image data corresponding to the image of the specified person. Further, the estimation unit 113 measures the body surface temperature of the person specified from the extracted thermal image data. The estimation unit 113 may measure the body surface temperature from the portion showing the highest temperature in the extracted thermal image data. Further, the estimation unit 113 may calculate a statistical value of the temperature of the extracted thermal image data and use the calculated statistical value as the body surface temperature of a person.
- the estimation unit 113 estimates the possibility of developing a person by using the body surface temperature of the person measured from the thermal image data. More specifically, for example, the estimation unit 113 measures the body surface temperature of the specified person, and when the measured value is equal to or higher than a preset threshold value (for example, 37.5 degrees Celsius), the possibility of developing an infectious disease is possible. Is presumed to have. Further, the estimation unit 113 may estimate the possibility of developing an infectious disease in consideration of the measured body surface temperature described above and the symptom behavior described later.
- a preset threshold value for example, 37.5 degrees Celsius
- the estimation unit 113 When the estimation unit 113 receives the visible light image data, the estimation unit 113 detects the operating state of the person from the image data of the person included in the received visible light image data. Then, the estimation unit 113 reads the symptom operation database 121 stored in the storage unit 120. Further, the estimation unit 113 collates the detected motion state of the person with the symptom motion pattern included in the symptom motion database 121, and collates whether or not the motion state of the person matches the symptom motion related to the onset of an infectious disease. do. As a result, the estimation unit 113 estimates the possibility of developing a person.
- the estimation unit 113 estimates that the person has a possibility of developing an infectious disease when the movement state of the person matches the symptomatic movement related to the onset of the infectious disease. More specifically, for example, the estimation unit 113 detects an action of a person identified from image data to cough or sneeze.
- the symptom motion database 121 stores motion patterns in which a person coughs or sneezes. The estimation unit 113 collates the detected motion with the symptom motion pattern, and if they match, it estimates that the person involved in the detected motion may have developed an infectious disease.
- the fact that the collation results match means that they are substantially the same, and the determination of the match can be appropriately set by those skilled in the art.
- the attention image detection unit 114 in the present embodiment detects that the person of interest and the surrounding person are performing the attention operation.
- the "attention movement” is a movement including at least one of a person's mouth movement, wearing a mask, coughing, sneezing, and contacting movement, and is a predetermined movement that is judged to increase the risk of infectious disease. Point to. For example, if a person is performing a violent mouth movement, the person is assumed to be talking.
- the attention image detection unit 114 detects that the attention person and the peripheral person perform such a attention operation in the image including the attention person and the peripheral person, the attention image detection unit 114 detects the attention image.
- the attention image detection unit 114 may detect the attention image by further considering the degree of congestion in the area including the person in the image related to the image data. In this case, the attention image detection unit 114 determines that the risk of infection of an infectious disease is relatively high when the degree of congestion is relatively high.
- the attention image detection unit 114 may calculate a predetermined population density as the degree of congestion from the relationship between the space and the number of people in the image data. Further, the attention image detection unit 114 may perform crowd detection on the image data as the degree of congestion.
- a crowd refers to a state in which a plurality of people appear to overlap in a predetermined space. In this case, the attention image detection unit 114 can detect the crowd, identify the crowded state of the detected crowd, and calculate the degree of congestion.
- the attention image detection unit 114 is set to detect one attention image from the period in which the attention person and the peripheral person exist. You may. As a result, the attention image detection unit 114 can suppress the redundant detection of the attention image.
- the storage unit 120 is a storage device including a non-volatile memory such as an EPROM (ErasableProgrammableReadOnlyMemory) or a flash memory.
- the storage unit 120 stores the symptom operation database 121.
- the symptom movement database 121 is a database for estimating the possibility of developing an infectious disease, and includes a symptom movement pattern of a person who has developed an infectious disease. As described above, the storage unit 120 appropriately supplies the symptom operation database 121 to the estimation unit 113.
- the symptom operation database 121 may include a plurality of symptom operation patterns. Further, the data included in the symptom operation database 121 may be updated as appropriate.
- FIG. 4 is a block diagram of the image display system 1 according to the second embodiment.
- the image display system 1 is installed for the purpose of grasping the risk of infection of a person in the facility 900.
- the image display system 1 has an image display device 20, an image display device, a visible light camera 300, and a thermal camera 400 as main configurations.
- the visible light camera 300 and the thermal camera 400 are fixed at a predetermined position of the facility 900, and photograph a person in the facility 900.
- the visible light camera 300 and the thermal camera 400 are communicably connected to the image display device 20 via the network N1 which is a communication network.
- the visible light camera 300 photographs a person P1 and a person P2 with an angle of view shown by a dotted line, generates visible light image data, and supplies the visible light image data to the image display device 20.
- the thermal camera 400 captures a person P1 and a person P2 with an angle of view indicated by a two-dot chain line, generates thermal image data, and supplies the image to the image display device 20.
- the image display device 20 shown in FIG. 4 is connected to the visible light camera 300 via the network N1 and receives visible light image data. Further, the image display device 20 is connected to the thermal camera 400 via the network N1 and receives thermal image data. Further, the image display device 20 is communicably connected to the display 200, and outputs image data related to a series of image groups via the output unit 115. In the example shown in the figure, the visible light camera 300 and the thermal camera 400 are shown one by one, but the number of these cameras may be plural.
- the image display system 1 can grasp the infection risk in a wide range of the facility 900 by taking pictures of different places by a plurality of cameras and supplying the image data taken by each to the image display device 20.
- the display 200 is a display device including, for example, a liquid crystal display or organic electroluminescence.
- the display 200 is communicably connected to the image display device 20, receives image data from the image display device 20, and displays the received image data.
- the image display device 20 and the display 200 are connected not via the network N1, but may be connected via the network N1.
- FIG. 5 is a diagram showing an example of an image group extracted by the image display device according to the second embodiment.
- an arrow extending horizontally from left to right indicates the passage of time.
- the imaging period V20 is shown as the band shape extending parallel to the arrow.
- the shooting period V20 schematically shows a period in which a plurality of images, that is, moving images taken by the visible light camera 300 are continuously generated.
- the first period Q1 and the second period Q2 extending in the left-right direction are shown in the shooting period V20.
- the first period Q1 indicates a period in which the person P1 is included in the image taken by the visible light camera 300.
- the second period Q2 indicates a period in which the person P2 is included in the image taken by the visible light camera 300.
- the first period Q1 indicates the time between the time T1 and the time T7.
- the second period Q2 indicates the time between the time T2 after the time T1 and the time T6 before the time T7.
- the extraction period V21 shown in bold is superimposed on the central part of the band shape V20.
- the extraction period V21 is a period during which the person P1 and the person P2 are close to each other, and indicates a period during which a series of images extracted by the output unit 115 are captured. More specifically, the extraction period V21 indicates the period from the time T3 after the time T3 to the time T5 before the time T6. At the center of the extraction period V21, the attention time V22 indicated by hatching is shown.
- the time of interest V22 is the time T4 after the time T3 and before the time T5.
- the time T4 is the time when the attention image detected by the attention image detection unit 114 was taken. That is, at time T4, the person P1 and the person P2 are in the closest state, for example, and the risk of infection is determined to be high. Therefore, the attention image detection unit 114 detected the image taken at the time T4 as the attention image. Further, the output unit 115 extracts a preset period (that is, from time T3 to time T5) before and after the time when the image of interest is taken as a series of image groups.
- the image group extracted by the image display device 20 has been described above.
- the above-mentioned method for extracting an image group is only an example, and the image group extracted by the output unit 115 is not limited to the above-mentioned method.
- the output unit 115 may extract the period during which the person P2 is included in the angle of view, that is, between the time T2 and the time T6. Further, the output unit 115 may extract the period during which the person P1 is included in the angle of view, that is, between the time T1 and the time T7.
- the output unit 115 may change the frame rate and image quality of the image data when extracting a series of image groups.
- the embodiment 2 has been described above.
- the image display device 20 and the image display system 1 according to the second embodiment detect a person of interest showing symptoms of an infectious disease in a place where a plurality of people come and go, and further infect a person existing in the vicinity of the person of interest. Can display images that include situations where can be transmitted. Therefore, according to the second embodiment, it is possible to provide an image display device, an image display system, or the like that suitably displays a situation with a high risk of infection.
- FIG. 6 is a block diagram of the image display device 30 according to the third embodiment.
- the image display device 30 shown in FIG. 6 is different from the above-described embodiment in that the storage unit 120 stores the authentication database. Further, in the image display device 30 shown in FIG. 6, the processing performed by the specific unit 112 is different from the above-described embodiment.
- the authentication database 122 includes a person's authentication data and a person's attribute data.
- the authentication data is data used for authentication performed by the specific unit 112.
- the authentication data is data for identifying a feature peculiar to a person, and is, for example, feature data of a face image.
- the authentication data may be iris data or ear shape data.
- Attribute data is data that accompanies a person involved in authentication and is used when determining the risk of being infected with an infectious disease.
- the attribute data may include antibody certification data possessed by the person involved in the authentication.
- the antibody certification data is data indicating whether or not the antibody has an infectious disease.
- the attribute data may also be a history of the person involved in the authentication related to the infectious disease or other information related to the resistance of the person involved in the authentication to the infectious disease.
- the specific unit 112 in the present embodiment not only identifies the person but also authenticates the person using the authentication data.
- the identification unit 112 uses the authentication data included in the authentication database 122 when identifying a person.
- the identification unit 112 supplies the authentication result to the estimation unit 113.
- the estimation unit 113 estimates the possibility of infection of the person to be authenticated from the data received from the specific unit 112.
- the estimation unit 113 has antibody certification when the body surface temperature of the person to be authenticated is equal to or higher than the threshold value or when the person performs an operation that matches the symptom operation pattern. If so, it is determined whether or not the patient is showing symptoms after taking this into consideration. That is, when the body surface temperature of the person having the antibody certification is equal to or higher than the threshold value, or when the person having the antibody certification performs an action that matches the symptom movement pattern, the estimation unit 113 tells the estimation unit 113 that the person has a symptom of an infectious disease. It may not be determined that it may indicate.
- the attention image detection unit 114 in the present embodiment detects the attention image based on the attribute data. For example, the attention image detection unit 114 detects the attention image by adding the antibody certification data of the person to be authenticated. More specifically, when a peripheral person existing near the person of interest has an antibody proof, the attention image detection unit 114 does not determine that the possibility of infection is high for this peripheral person. Therefore, even if a person having this antibody certification exists near the person of interest, the attention image detection unit 114 may not detect the person of interest as the image of interest.
- the embodiment 3 has been described above.
- the image display device 30 according to the third embodiment detects a person of interest showing symptoms of an infectious disease in a place where a plurality of people come and go, and there is a possibility that the infectious disease is transmitted to a person existing in the vicinity of the person of interest. You can display an image that includes a certain situation. Further, the image display device 30 performs processing after adding the attribute data of the person to be authenticated at the time of detecting the person of interest and extracting the image of interest. Therefore, according to the third embodiment, it is possible to provide an image display device or the like that suitably displays a situation with a high risk of infection, taking into consideration the individual circumstances of the person.
- FIG. 7 is a block diagram of the image display device 40 according to the fourth embodiment.
- the attention image detection unit 114 in the present embodiment detects the attention image in consideration of the infection risk index related to the shooting location of the acquired image data. For example, when there is an image in which a person of interest and a peripheral person are in contact with each other in a place where the infection index is relatively high, and an image in which similar contact is made in a place where the infection index is relatively low, the image detection unit of interest is present. 114 may detect the former as an image of interest and may not detect the latter.
- the storage unit 120 in the present embodiment stores the index database 123.
- the index database 123 is a database including an infection risk index relating to the shooting location of the acquired image data.
- the index database 123 is associated with a camera that shoots a predetermined shooting location, and is a preset value.
- the infection risk index associated with outdoor image data is set lower than the infection risk index associated with indoor image data.
- the infection risk index associated with the image data in a relatively narrow space is set higher than the infection risk index associated with the image data in a relatively wide space.
- the infection risk index may be set higher in a place where the air flow is relatively poor than in a place where the air flow is relatively good, for example, depending on the ventilation condition of the room or the shape of the room. ..
- different infection risk indexes may be set for different shooting areas in the image data taken by one camera.
- the infection risk index may be updated as appropriate. For example, when the attention person stays in the same place for a period longer than a preset period, the attention image detection unit 114 temporarily sets the infection risk index of the place where the attention person stays high. You may. In this case, the attention image detection unit 114 may detect the attention region in which the attention person stays for a period equal to or longer than a preset period, and may detect an image in which a peripheral person exists in the attention region as the attention image. ..
- the embodiment 4 has been described above.
- the image display device 40 performs processing in consideration of the infection risk index applied to the photographing location when extracting the image of interest. Therefore, according to the fourth embodiment, it is possible to provide an image display device or the like that suitably displays a situation with a high risk of infection, taking into consideration the circumstances of the shooting location.
- FIG. 8 is a block diagram of the image display device 50 according to the fifth embodiment.
- the image display device 50 has an audio data acquisition unit 117.
- the audio data acquisition unit 117 acquires audio data generated by collecting sound from a microphone installed in the image data shooting area.
- the voice data acquisition unit 117 supplies the acquired voice data to the estimation unit 113 and the attention image detection unit 114.
- the estimation unit 113 in the present embodiment estimates the possibility of onset from the voice emitted by the specified person. For example, the estimation unit 113 extracts the voice estimated to be emitted by the specified person from the voice data received from the voice data acquisition unit 117. At this time, the estimation unit 113 may analyze the visible light image data or the thermal image data in addition to the audio data. When the identified person is coughing or sneezing, the estimation unit 113 associates this with the symptom movement pattern.
- the attention image detection unit 114 in the present embodiment receives voice data from the voice data acquisition unit 117, and detects the voice emitted by the person of interest and the surrounding person from the received voice data. Then, it is detected that the attention person is coughing or sneezing near the surrounding person, the attention person is talking to the surrounding person, or the person is making a loud voice. At this time, the attention image detection unit 114 may detect the above-mentioned sound after analyzing the postures of the body of the person of interest and the surrounding person in the visible light image data or the thermal image data. By such a method, the attention image detection unit 114 detects the attention image from the image data.
- the embodiment 5 has been described above.
- the image display device 50 uses voice data when determining a person of interest or when detecting an image of interest. As a result, the image display device 50 improves the accuracy for displaying a desired image. Therefore, according to the fifth embodiment, it is possible to provide an image display device or the like that accurately displays a situation with a high risk of infection.
- FIG. 9 is a block diagram of the image display device 60 according to the sixth embodiment.
- the image display device 60 has an attention level setting unit 118.
- the attention level setting unit 118 sets the attention level for the attention image.
- the degree of attention is an index when displaying a series of image groups, and can also be called a display priority.
- the degree of attention is indicated by, for example, a numerical value in a predetermined range.
- the predetermined range may be a range of several stages such as 0, 1, and 2. For example, the higher the attention of the image group, the higher the possibility that the infectious disease is transmitted to the surrounding people.
- the attention level setting unit 118 analyzes the contact state between the person of interest and a peripheral person, and sets the degree of attention according to the result of the analysis.
- the attention level setting unit 118 talks about the attention level (first attention level) of an image in which the attention person and the surrounding person are talking facing each other at a close distance, and the attention person and the surrounding person talk. Set it higher than the attention level (second attention level) of the image that has not been set.
- the attention level setting unit 118 is not crowded when a large number of people are present and the attention person and the surrounding people are facing each other in a crowded situation. Set the degree of attention higher than that.
- the degree of attention is set higher than that of the case where the person wearing the mask is worn.
- the degree of attention is higher than the similar situation in the place where the infection risk index is low. Is set high.
- the output unit 115 sets the display priority higher for the image group having a higher degree of attention and outputs the image group. That is, the output unit 115 preferentially outputs the image group set to the first attention level having a relatively high attention level to the image group set to the second attention level having a relatively low attention level.
- FIG. 10 is a flowchart showing the image display method according to the sixth embodiment.
- the flowchart shown in FIG. 10 is different from the flowchart shown in FIG. 2 in that steps S21 and S22 are added between steps S14 and S15.
- step S14 the attention image detection unit 114 detects the attention image including the attention person having a possibility of onset and the peripheral person in the vicinity of the attention person from the estimation result received from the estimation unit 113 (step S14). ). The attention image detection unit 114 supplies the detected attention image to the output unit 115 and the attention level setting unit 118.
- the attention level setting unit 118 sets the attention level for the attention image received from the attention image detection unit 114 (step S21).
- the attention level setting unit 118 supplies the attention level set for the attention image to the output unit 115.
- the output unit 115 sets the display order of the attention image according to the set attention degree (step S22).
- the output unit 115 extracts a series of image groups including the attention image from the attention image received from the attention image detection unit 114, and outputs the extracted series of image groups to the display device in the above-mentioned display order. Step S15).
- the processing performed by the image display device 60 has been described above.
- the image display device 60 outputs these in descending order of attention.
- the output unit 115 outputs a plurality of image groups according to the display order set according to the degree of attention, but the output process may be sequentially performed according to the user's operation.
- FIG. 11 is a diagram showing an example of an image displayed by the image display device 60 according to the sixth embodiment.
- FIG. 11 shows an image 201 displayed by the display device.
- Image 201 shows a map of the facility on the upper side.
- the in-facility map shows the installation positions of the cameras 301, 302, and 303, respectively, and the areas A, B, and C as the shooting range of each camera.
- an icon described as ID # 1011 is shown in the area A.
- an icon described as ID # 1012 is shown in area B.
- An icon with ID # 1013 is shown in Area C. This indicates that the image group of ID # 1013 is extracted in Area C.
- the user who visually recognizes the image 201 can play back each moving image by selecting the icon shown on the map in the facility.
- Image 201 shows a video list at the bottom.
- the moving image list the moving image IDs # 1011, # 1012 and # 1013 are displayed. Each video shows the corresponding shooting date, shooting area, and attention level.
- the moving image ID # 1012 corresponding to the attention level “1” has the highest attention level.
- the moving image ID # 1011 corresponding to the attention level “2” has the second highest attention level.
- the moving image ID # 1013 corresponding to the attention level "3" has the third highest attention level.
- the user who visually recognizes the image 201 can play the moving image in the order of attention.
- the user can also play the selected video regardless of the degree of attention.
- the embodiment 6 has been described above.
- the image display device 60 can suitably output a desired image group by setting the degree of attention. Therefore, according to the sixth embodiment, it is possible to provide an image display device or the like that efficiently displays a situation with a high risk of infection.
- Non-temporary computer-readable media include various types of tangible recording media.
- Examples of non-temporary computer-readable media include magnetic recording media (eg, flexible disks, magnetic tapes, hard disk drives), optomagnetic recording media (eg, optomagnetic disks), CD-ROM (Read Only Memory) CD-R, CDs. -R / W, including semiconductor memory (for example, mask ROM, PROM (Programmable ROM), EPROM (Erasable PROM), flash ROM, RAM (RandomAccessMemory)).
- the program may also be supplied to the computer by various types of temporary computer-readable media. Examples of temporary computer readable media include electrical, optical, and electromagnetic waves.
- the temporary computer-readable medium can supply the program to the computer via a wired communication path such as an electric wire and an optical fiber, or a wireless communication path.
- Image data acquisition means for acquiring multiple image data from the camera, Specific means for identifying a person from the image data and An estimation means for estimating the possibility of developing an infectious disease of the person identified from the image data, and Based on the estimation result, the attention image detecting means for detecting the attention image including the attention person having the possibility of onset and the peripheral person in the vicinity of the attention person, and the attention image detecting means.
- An image display device including an output means for extracting and outputting a series of image groups including the attention image.
- the estimation means estimates the possibility of onset based on the body surface temperature of the person measured from the thermal image data corresponding to the image data.
- the image display device according to Appendix 1. (Appendix 3) Further equipped with symptom-motion memory means to memorize symptom-motion when an infectious disease develops, The estimation means estimates the possibility of onset by detecting an action in the specified person and collating whether or not the detected action matches the symptom action.
- the image display device according to Appendix 1 or 2. (Appendix 4)
- the symptom movement storage means stores the coughing or sneezing movement of the person as the symptom movement, and stores the coughing or sneezing movement.
- the estimation means detects a coughing or sneezing motion of the person.
- the image display device according to Appendix 3. (Appendix 5)
- the attention image detecting means detects as the attention image an image in which the attention person and the peripheral person exist at a distance less than a threshold value for a predetermined period or longer.
- the image display device according to any one of Supplementary note 1 to 4. (Appendix 6)
- the attention image detecting means detects an attention movement including at least one of mouth movement, mask wearing, coughing, sneezing, and contact movement of the attention person and the peripheral person, and the attention image is based on the attention movement. To detect, The image display device according to any one of Supplementary note 1 to 5.
- the attention image detecting means detects the attention image by further considering the degree of congestion in the region including the person in the image related to the image data.
- the image display device according to any one of Supplementary note 1 to 6.
- (Appendix 8) Further provided with an authentication data storage means for storing the authentication data of the person and the attribute data of the person.
- the specific means also authenticates the person based on the authentication data, and performs the authentication.
- the attention image detecting means detects the attention image based on the attribute data.
- the image display device according to any one of Supplementary note 1 to 7.
- the authentication data storage means includes the antibody certification data possessed by the person in the attribute data.
- the attention image detecting means detects the attention image by adding the antibody certification data of the person to be authenticated.
- the image display device according to Appendix 8. (Appendix 10) Further provided with an index storage means for storing the infection risk index regarding the shooting location of the image data to be acquired.
- the attention image detecting means detects the attention image in consideration of the infection risk index relating to the shooting location of the image data to be acquired.
- the image display device according to any one of Supplementary note 1 to 9. (Appendix 11)
- the attention image detecting means detects an attention region in which the attention person stays for a period equal to or longer than a preset period, and detects an image in which the peripheral person exists in the attention region as the attention image.
- the image display device according to any one of Supplementary note 1 to 10.
- the estimation means estimates the possibility of onset based on the voice emitted by the person.
- the image display device according to any one of Supplementary note 1 to 11.
- the attention image detecting means detects the attention image based on the voices emitted by the attention person and the peripheral person.
- the image display device according to any one of Supplementary note 1 to 12.
- (Appendix 14) Further provided with an attention level setting means for setting the attention level based on the contact state between the attention person and the peripheral person with respect to the attention image.
- the output means outputs a series of images based on the degree of attention.
- the image display device according to any one of Supplementary note 1 to 13.
- the output means outputs a series of images based on the degree of attention.
- the image display device according to any one of Supplementary note 1 to 13.
- the attention level setting means sets the priority of the image group to be displayed higher as the attention level is higher.
- the output means preferentially outputs the image group set to the first attention level having a relatively high attention level to the image group set to a second attention level having a relatively low attention level. do, The image display device according to Appendix 14 or 15.
- Appendix 17 The image display device according to any one of Supplementary note 1 to 16 and the image display device.
- An image display system including at least one of a camera that supplies the image data to the image data acquisition means or a display device that receives and displays the image group from the output means.
- the computer Acquire multiple image data from the camera and Identify a person from the image data and Estimating the possibility of developing an infectious disease in the identified person, Based on the estimation result, a attention image including the attention person having the possibility of developing the disease and a peripheral person in the vicinity of the attention person is detected. Extracting and outputting a series of images including the above-mentioned attention image, Image display method.
- image display system 10 image display device 20 image display device 30 image display device 40 image display device 50 image display device 60 image display device 111 image data acquisition unit 112 specific unit 113 estimation unit 114 attention image detection unit 115 output unit 116 thermal image Data acquisition unit 117 Voice data acquisition unit 118 Attention setting unit 120 Storage unit 121 Symptom operation database 122 Authentication database 123 Index database 200 Display 300 Visible light camera 400 Thermal camera 900 Facility N1 Network P1 Person P2 Person
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Abstract
Description
以下、図面を参照して本発明の実施の形態について説明する。図1は、実施の形態1にかかる画像表示装置10のブロック図である。図1に示す画像表示装置10は、所定の施設内または屋外に設置されたカメラに接続し、カメラが撮影した画像データを取得して、注目すべき画像ないし画像群を表示する。画像表示装置10は主な構成として画像データ取得部111、特定部112、推定部113、注目画像検出部114および出力部115を有する。
次に、実施の形態2について説明する。図3は、実施の形態2にかかる画像表示装置20のブロック図である。図3に示す画像表示装置20は、熱画像データ取得部116および記憶部120を有する点が、実施の形態1と異なる。
次に、実施の形態3について説明する。図6は、実施の形態3にかかる画像表示装置30のブロック図である。図6に示す画像表示装置30は、記憶部120が認証データベースを記憶する点が、上述の実施の形態と異なる。また図6に示す画像表示装置30は、特定部112が行う処理が上述の実施の形態と異なる。
次に、実施の形態4について説明する。実施の形態4にかかる画像表示装置40は、記憶部120が指数データベース123を記憶している点、および注目画像検出部114が指数データベース123を利用する点が上述の実施の形態と異なる。図7は、実施の形態4にかかる画像表示装置40のブロック図である。
次に、実施の形態5について説明する。実施の形態5にかかる画像表示装置は、音声データ取得部を有する点、および注目人物の検出や注目画像の検出の際に音声データを利用する点が、上述の実施の形態と異なる。図8は、実施の形態5にかかる画像表示装置50のブロック図である。
次に、実施の形態6について説明する。実施の形態6は、注目度設定部を有する点が、上述の実施の形態と異なる。図9は、実施の形態6にかかる画像表示装置60のブロック図である。画像表示装置60は、注目度設定部118を有する。
(付記1)
カメラから複数の画像データを取得する画像データ取得手段と、
前記画像データから人物を特定する特定手段と、
前記画像データから特定した前記人物の感染症の発症可能性を推定する推定手段と、
前記推定の結果に基づいて、前記発症可能性を有する注目人物と当該注目人物の周辺に周辺人物とが含まれる注目画像を検出する注目画像検出手段と、
前記注目画像を含む一連の画像群を抽出して出力する出力手段と、を備える
画像表示装置。
(付記2)
赤外線カメラから熱画像データを取得する熱画像データ取得手段をさらに備え、
前記推定手段は、前記画像データに対応する前記熱画像データから測定した前記人物の体表温度に基づいて前記発症可能性を推定する、
付記1に記載の画像表示装置。
(付記3)
感染症を発症した場合の症状動作を記憶する症状動作記憶手段をさらに備え、
前記推定手段は、特定した前記人物における動作を検出し、検出した前記動作が前記症状動作に一致するか否かを照合することにより前記発症可能性を推定する、
付記1または2に記載の画像表示装置。
(付記4)
前記症状動作記憶手段は、前記人物の咳またはくしゃみ動作を前記症状動作として記憶し、
前記推定手段は、前記人物の咳またはくしゃみ動作を検出する、
付記3に記載の画像表示装置。
(付記5)
前記注目画像検出手段は、前記注目人物と前記周辺人物とが閾値未満の距離に所定期間以上存在する画像を前記注目画像として検出する、
付記1~4のいずれか一項に記載の画像表示装置。
(付記6)
前記注目画像検出手段は、前記注目人物および前記周辺人物の口の動き、マスクの装着、咳、くしゃみ、接触動作の少なくとも1つを含む注目動作を検出し、前記注目動作に基づいて前記注目画像を検出する、
付記1~5のいずれか一項に記載の画像表示装置。
(付記7)
前記注目画像検出手段は、前記画像データにかかる画像における前記人物が含まれる領域の混雑度をさらに加味して前記注目画像を検出する、
付記1~6のいずれか一項に記載の画像表示装置。
(付記8)
前記人物の認証データおよび前記人物の属性データを記憶する認証データ記憶手段をさらに備え、
前記特定手段は前記認証データに基づいて前記人物の認証を併せて行い、
前記注目画像検出手段は、前記属性データに基づいて前記注目画像を検出する、
付記1~7のいずれか一項に記載の画像表示装置。
(付記9)
前記認証データ記憶手段は、前記属性データに前記人物が有する抗体証明データを含み、
前記注目画像検出手段は、前記認証にかかる前記人物の前記抗体証明データを加味して前記注目画像を検出する、
付記8に記載の画像表示装置。
(付記10)
取得する前記画像データの撮影場所に関する感染リスク指数を記憶する指数記憶手段をさらに備え、
前記注目画像検出手段は、取得する前記画像データの撮影場所に関する前記感染リスク指数を加味して前記注目画像を検出する、
付記1~9のいずれか一項に記載の画像表示装置。
(付記11)
前記注目画像検出手段は、予め設定した期間以上の期間を前記注目人物が留まっていた注目領域を検出し、前記注目領域に前記周辺人物が存在している画像を前記注目画像として検出する、
付記1~10のいずれか一項に記載の画像表示装置。
(付記12)
前記画像データの撮影領域における音声データを取得する音声データ取得手段をさらに備え、
前記推定手段は、前記人物が発する音声に基づいて前記発症可能性を推定する、
付記1~11のいずれか一項に記載の画像表示装置。
(付記13)
前記注目画像検出手段は、前記注目人物および前記周辺人物が発する音声に基づいて前記注目画像を検出する、
付記1~12のいずれか一項に記載の画像表示装置。
(付記14)
前記注目画像に対して前記注目人物と前記周辺人物との接触状態に基づいて注目度を設定する注目度設定手段をさらに備え、
前記出力手段は、前記注目度に基づいて、一連の画像群を出力する、
付記1~13のいずれか一項に記載の画像表示装置。
(付記15)
前記注目画像に対して前記周辺人物の感染リスクを推定し、前記感染リスクに基づいて注目度を設定する注目度設定手段をさらに備え、
前記出力手段は、前記注目度に基づいて、一連の画像群を出力する、
付記1~13のいずれか一項に記載の画像表示装置。
(付記16)
前記注目度設定手段は、前記注目度が高いほど表示する前記画像群の優先度を高く設定し、
前記出力手段は、相対的に前記注目度が高い第1注目度に設定された前記画像群を、相対的に前記注目度が低い第2注目度に設定された前記画像群より優先的に出力する、
付記14または15に記載の画像表示装置。
(付記17)
付記1~16のいずれか一項に記載の画像表示装置と、
前記画像データを前記画像データ取得手段に供給するカメラまたは前記出力手段から前記画像群を受け取って表示する表示装置の少なくともいずれか一方と、を備える
画像表示システム。
(付記18)
コンピュータが、
カメラから複数の画像データを取得し、
前記画像データから人物を特定し、
特定した前記人物における感染症の発症可能性を推定し、
前記推定の結果に基づいて、前記発症可能性を有する注目人物と当該注目人物の周辺に周辺人物とが含まれる注目画像を検出し、
前記注目画像を含む一連の画像群を抽出して出力する、
画像表示方法。
(付記19)
コンピュータに、
カメラから複数の画像データを取得する処理と、
前記画像データから人物を特定する処理と、
特定した前記人物における感染症の発症可能性を推定する処理と、
前記推定の結果に基づいて、前記発症可能性を有する注目人物と当該注目人物の周辺に周辺人物とが含まれる注目画像を検出する処理と、
前記注目画像を含む一連の画像群を抽出して出力する処理と、を備える画像表示方法を実行させる
プログラムを、コンピュータに実行させるプログラムが格納された非一時的なコンピュータ可読媒体。
10 画像表示装置
20 画像表示装置
30 画像表示装置
40 画像表示装置
50 画像表示装置
60 画像表示装置
111 画像データ取得部
112 特定部
113 推定部
114 注目画像検出部
115 出力部
116 熱画像データ取得部
117 音声データ取得部
118 注目度設定部
120 記憶部
121 症状動作データベース
122 認証データベース
123 指数データベース
200 ディスプレイ
300 可視光カメラ
400 サーマルカメラ
900 施設
N1 ネットワーク
P1 人物
P2 人物
Claims (19)
- カメラから複数の画像データを取得する画像データ取得手段と、
前記画像データから人物を特定する特定手段と、
前記画像データから特定した前記人物の感染症の発症可能性を推定する推定手段と、
前記推定の結果に基づいて、前記発症可能性を有する注目人物と当該注目人物の周辺に周辺人物とが含まれる注目画像を検出する注目画像検出手段と、
前記注目画像を含む一連の画像群を抽出して出力する出力手段と、を備える
画像表示装置。 - 赤外線カメラから熱画像データを取得する熱画像データ取得手段をさらに備え、
前記推定手段は、前記画像データに対応する前記熱画像データから測定した前記人物の体表温度に基づいて前記発症可能性を推定する、
請求項1に記載の画像表示装置。 - 感染症を発症した場合の症状動作を記憶する症状動作記憶手段をさらに備え、
前記推定手段は、特定した前記人物における動作を検出し、検出した前記動作が前記症状動作に一致するか否かを照合することにより前記発症可能性を推定する、
請求項1または2に記載の画像表示装置。 - 前記症状動作記憶手段は、前記人物の咳またはくしゃみ動作を前記症状動作として記憶し、
前記推定手段は、前記人物の咳またはくしゃみ動作を検出する、
請求項3に記載の画像表示装置。 - 前記注目画像検出手段は、前記注目人物と前記周辺人物とが閾値未満の距離に所定期間以上存在する画像を前記注目画像として検出する、
請求項1~4のいずれか一項に記載の画像表示装置。 - 前記注目画像検出手段は、前記注目人物および前記周辺人物の口の動き、マスクの装着、咳、くしゃみ、接触動作の少なくとも1つを含む注目動作を検出し、前記注目動作に基づいて前記注目画像を検出する、
請求項1~5のいずれか一項に記載の画像表示装置。 - 前記注目画像検出手段は、前記画像データにかかる画像における前記人物が含まれる領域の混雑度をさらに加味して前記注目画像を検出する、
請求項1~6のいずれか一項に記載の画像表示装置。 - 前記人物の認証データおよび前記人物の属性データを記憶する認証データ記憶手段をさらに備え、
前記特定手段は前記認証データに基づいて前記人物の認証を併せて行い、
前記注目画像検出手段は、前記属性データに基づいて前記注目画像を検出する、
請求項1~7のいずれか一項に記載の画像表示装置。 - 前記認証データ記憶手段は、前記属性データに前記人物が有する抗体証明データを含み、
前記注目画像検出手段は、前記認証にかかる前記人物の前記抗体証明データを加味して前記注目画像を検出する、
請求項8に記載の画像表示装置。 - 取得する前記画像データの撮影場所に関する感染リスク指数を記憶する指数記憶手段をさらに備え、
前記注目画像検出手段は、取得する前記画像データの撮影場所に関する前記感染リスク指数を加味して前記注目画像を検出する、
請求項1~9のいずれか一項に記載の画像表示装置。 - 前記注目画像検出手段は、予め設定した期間以上の期間を前記注目人物が留まっていた注目領域を検出し、前記注目領域に前記周辺人物が存在している画像を前記注目画像として検出する、
請求項1~10のいずれか一項に記載の画像表示装置。 - 前記画像データの撮影領域における音声データを取得する音声データ取得手段をさらに備え、
前記推定手段は、前記人物が発する音声に基づいて前記発症可能性を推定する、
請求項1~11のいずれか一項に記載の画像表示装置。 - 前記注目画像検出手段は、前記注目人物および前記周辺人物が発する音声に基づいて前記注目画像を検出する、
請求項1~12のいずれか一項に記載の画像表示装置。 - 前記注目画像に対して前記注目人物と前記周辺人物との接触状態に基づいて注目度を設定する注目度設定手段をさらに備え、
前記出力手段は、前記注目度に基づいて、一連の画像群を出力する、
請求項1~13のいずれか一項に記載の画像表示装置。 - 前記注目画像に対して前記周辺人物の感染リスクを推定し、前記感染リスクに基づいて注目度を設定する注目度設定手段をさらに備え、
前記出力手段は、前記注目度に基づいて、一連の画像群を出力する、
請求項1~13のいずれか一項に記載の画像表示装置。 - 前記注目度設定手段は、前記注目度が高いほど表示する前記画像群の優先度を高く設定し、
前記出力手段は、相対的に前記注目度が高い第1注目度に設定された前記画像群を、相対的に前記注目度が低い第2注目度に設定された前記画像群より優先的に出力する、
請求項14または15に記載の画像表示装置。 - 請求項1~16のいずれか一項に記載の画像表示装置と、
前記画像データを前記画像データ取得手段に供給するカメラまたは前記出力手段から前記画像群を受け取って表示する表示装置の少なくともいずれか一方と、を備える
画像表示システム。 - コンピュータが、
カメラから複数の画像データを取得し、
前記画像データから人物を特定し、
特定した前記人物における感染症の発症可能性を推定し、
前記推定の結果に基づいて、前記発症可能性を有する注目人物と当該注目人物の周辺に周辺人物とが含まれる注目画像を検出し、
前記注目画像を含む一連の画像群を抽出して出力する、
画像表示方法。 - コンピュータに、
カメラから複数の画像データを取得する処理と、
前記画像データから人物を特定する処理と、
特定した前記人物における感染症の発症可能性を推定する処理と、
前記推定の結果に基づいて、前記発症可能性を有する注目人物と当該注目人物の周辺に周辺人物とが含まれる注目画像を検出する処理と、
前記注目画像を含む一連の画像群を抽出して出力する処理と、を備える画像表示方法を実行させる
プログラムを、コンピュータに実行させるプログラムが格納された非一時的なコンピュータ可読媒体。
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WO2019239813A1 (ja) * | 2018-06-14 | 2019-12-19 | パナソニックIpマネジメント株式会社 | 情報処理方法、情報処理プログラム及び情報処理システム |
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