CN108924648B - Method, apparatus, device and medium for playing video data to a user - Google Patents
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Abstract
Embodiments of the present disclosure provide methods, apparatuses, devices, and media for playing video data to a user. In one embodiment, a method of playing video data to a user includes: during playing of first video data to a user, behavior data of the user is collected, a candidate set including candidate video data to be provided after starting playing of the first video data is acquired, second video data to be played to the user is determined from the candidate set based on the behavior data, and the second video data is played to the user. By the method, the content of the video data played to the user can be adjusted according to the behavior of the user, so that the flexibility of playing the video data to the user is enhanced, the video playing efficiency is improved, and the user experience is greatly improved.
Description
Technical Field
Embodiments of the present disclosure relate to the field of video playback, and more particularly, to methods, apparatuses, and computer program products for playing video data to a user.
Background
With the development of computer technology, there are many scenes where videos are played to users. Typically, for example, in an educational setting, manual lectures are often replaced by playing teaching videos to users (i.e., students). The traditional video teaching mode is performed by a teacher recording teaching video in advance and then playing the teaching video to students at a given time, and the mode is generally called recording and playing. Sometimes, in order to increase the course experience, a recorded broadcast plus live broadcast mode is adopted, that is, in the process of playing videos for students, a teacher is additionally added to the classroom where the students are located to assist video management and teaching management.
However, both the recording and broadcasting method and the video providing method with auxiliary management of recording and broadcasting and teachers can only play the video recorded in advance to the user. The video can not be changed once being recorded, interaction between a teacher giving lessons and students is lacked, the content of the lessons can not be adjusted according to the performance of the students in a classroom, the video playing mode is inflexible, and the classroom experience of the students is not good.
Disclosure of Invention
Embodiments of the present disclosure provide a method, apparatus and computer program product for playing video data to a user.
In a first aspect of the present disclosure, a method for playing video data to a user is provided. The method comprises the following steps: during playing of first video data to a user, behavior data of the user is collected, a candidate set including candidate video data to be provided after starting playing of the first video data is acquired, second video data to be played to the user is determined from the candidate set based on the behavior data, and the second video data is played to the user.
In a second aspect of the present disclosure, an apparatus for playing video data to a user is provided. The apparatus comprises: a processor and a memory coupled with the processor. The memory has instructions stored therein that, when executed by the processor, cause the device to perform actions. The actions include: during the playing of first video data to a user, collecting behavior data of the user; obtaining a candidate set including candidate video data to be provided after starting to play the first video data; determining second video data to be played to the user from the candidate set based on the behavior data; and playing the second video data to the user.
In a third aspect of the disclosure, there is provided an apparatus comprising one or more processors; and storage means for storing the one or more programs which, when executed by the one or more processors, cause the one or more processors to carry out the method according to the first aspect of the disclosure.
In a fourth aspect of the present disclosure, a computer-readable medium is provided, on which a computer program is stored, which program, when executed by a processor, implements a method according to the first aspect of the present disclosure.
This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the disclosure, nor is it intended to be used to limit the scope of the disclosure.
Drawings
The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. In the drawings, like or similar reference characters designate like or similar elements, and wherein:
FIG. 1 illustrates a schematic diagram of a system architecture in which embodiments of the present disclosure may be implemented;
FIG. 2 shows a flow diagram of a method of playing video data to a user, according to an embodiment of the present disclosure;
FIG. 3 shows a schematic block diagram of a video profile according to an embodiment of the present disclosure
FIG. 4 shows a flow diagram of a method of playing video data to a user according to a further embodiment of the present disclosure;
FIG. 5 shows a schematic block diagram of an additional data profile according to an embodiment of the present disclosure;
FIG. 6 shows a block diagram of an apparatus for playing video data to a user, according to an embodiment of the present disclosure; and
FIG. 7 illustrates a block diagram of an example device that can be used to implement embodiments of the present disclosure.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of the present disclosure.
In describing embodiments of the present disclosure, the terms "include" and its derivatives should be interpreted as being inclusive, i.e., "including but not limited to. The term "based on" should be understood as "based at least in part on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The terms "first," "second," and the like may refer to different or the same object. Other explicit and implicit definitions are also possible below.
In the traditional video playing process, videos which are recorded in advance are played to users, and the played video content cannot be adjusted according to the behaviors and the reactions of the users, so that the playing mode of video data is not flexible, and interaction with the users is not possible. In scenarios where, for example, strong interaction with the user is required (e.g., video teaching scenarios), there is a lack of concern about the user's behavior, which may make the user experience poor. To address at least in part one or more of the above problems and other potential problems, embodiments of the present disclosure provide a method of playing video data to a user. In the method, the content of the video data played to the user can be adjusted according to the behavior of the user, so that the flexibility of playing the video data to the user is enhanced, and the user experience is greatly improved.
Fig. 1 illustrates a schematic diagram of a system architecture 100 in which embodiments of the present disclosure may be implemented. As shown in fig. 1, the system architecture 100 includes a video providing system 110 and an Artificial Intelligence (AI) system 120. The AI system 120 is operable to provide a preliminary analysis of user behavior to the video providing system 110 based on, among other things, the user's behavior (e.g., user audio data 140 and user video data 150). The video providing system 110 is configured to receive the video lesson data prepared in advance and determine the video data 160 to be played to the user based on a preliminary analysis of the user's behavior fed back from the AI system 120.
Since video teaching is a typical scene in which a video is played to a user, the following description will be given by taking a video teaching scene as an example. However, it should be understood that the technical solution according to the embodiments of the present disclosure may be fully applied to other scenarios, and the embodiments of the present disclosure are not limited in this respect.
In some embodiments, the video providing system 110 is for implementation on a client side, while the AI system 120 is for implementation on a server side. However, in other embodiments, the video providing system 110 may be implemented entirely or independently on the server side, and the AI system 120 may be implemented independently on the client side. Further, in some embodiments, the collected user audio data 140 and video data 150, as well as the video data 130 to be provided, may be stored on the server side. However, in other embodiments, such data may also be stored at the client. Embodiments of the invention are not limited in this respect.
In some embodiments, the user's actions (e.g., user audio data 140 and user video data 150) may be collected through specialized devices. For example, in a video teaching scenario, the user's actions may be collected by a recording device or camera installed in a classroom, and the collected data is the user's audio data 140 or the user's video data 150, respectively. In some embodiments, the collected data may also include environmental data such as the location where the user is located, e.g., classroom brightness, noise level, and the like. Embodiments of the present disclosure are not limited in this respect.
After such data (e.g., 140, 150) is collected, it is provided to the AI system 120 for preliminary analysis to obtain behavioral data for the user. The user's behavioral data may include, for example, the user's facial expressions, body gestures, voice data, and so forth. The user's facial expressions may, for example, reflect whether the user is focusing on what the teacher is currently teaching, while the speech data may, for example, reflect the situation where the user answers the teacher's question. In some embodiments, the behavioral data of the user may also include environmental data about the location where the user is located.
The user behavior data obtained by the AI system 120 analysis is then provided to the video providing system 110. The video providing system 110 also receives video data 130 to be provided. The video data 130 to be provided may be implemented as a division into a plurality of slices (not shown) that facilitate the video providing system 110 to purposefully select the slices from which to invoke the video data 160 for playback to the user based on the received behavior data of the user.
Specifically, the video providing system 110 may include a trigger 101, a decision processor 102, and a video data selector 103. The trigger 101 is configured to receive behavior data from a user of the AI system 120 and trigger the decision processor 102 based on the behavior data. The decision processor 102 is used to decide the content to be played (e.g., the video data 160 to be played to the user), the timing of the playing, and the manner of playing. The video data selector 103 is configured to call corresponding video data from the video data 130 to be provided according to the instruction of the decision processor 102, and finally play the called video data 160 played to the user.
It will be appreciated by those skilled in the art that the system architecture 100 shown in FIG. 1 is merely illustrative and may include more or fewer components depending on the functionality to be implemented. Embodiments of the present disclosure are not limited in this respect.
Embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. Fig. 2 shows a flow diagram of a method 200 for playing video data to a user, in accordance with an embodiment of the present disclosure. The method 200 may be implemented by the system architecture shown in fig. 1. For ease of discussion, the method 200 is discussed in conjunction with the system architecture of FIG. 1.
At block 210, during the playing of the first video data to the user, behavioral data of the user is collected. The first video data here is used to indicate data currently played to the user. In a video teaching scenario, the first video data may be a portion or a slice of a teaching video that represents at least a portion of the content of a teacher's lecture, for example. It should be understood by those skilled in the art that the "first video data" is provided only for convenience of description, and is used for distinguishing other video data such as the second video data in description, and is not intended as a specific limitation to the video content.
As described above with reference to fig. 1, the behavior data of the user may be collected by a camera or a recording device installed in a classroom and obtained through preliminary analysis by the AI system 120. In some embodiments, the behavioral data of the user may include at least any one of expression data, gesture data, voice data of the user, environmental data of a place where the user is located. These data may reflect the user's attention to the first video data being played, or feedback to the video data. Analyzing these data facilitates the accurate selection of the next video slice for playback that best matches or is most appropriate for the current student state.
Specifically, the facial expression data of the user may reflect, for example, whether the user is paying attention to a class and understanding the contents of the class; the sitting posture and posture (including head-down, head-up, etc.) of the user can reflect whether the user holds hands to answer questions or hold hands to ask questions, or leaves from the seat, etc., besides reflecting whether the user focuses attention to attend a class, for example; the user's voice data may, for example, reflect whether it is accurate to answer a question, whether a question is asked to a teacher, what the question is, and so on. And the environmental data of the location where the user is located may reflect, for example, whether the classroom is noisy, whether the classroom lighting is sufficient, etc.
It should be noted that the behavior data of the user does not have to be collected during the playing of the first video data to the user, but may be collected before and during the playing of the first video data to the user. In addition, the behavior data of the user may not stop after the first video is played. Embodiments of the present disclosure are not limited in this respect.
It is also noted that in some embodiments, the collected behavioral data of the user is not all the same. For example, behavioral data of the user to be collected may be determined based on the type of the first video data. In some embodiments, for example when the content type of the first video data is a teacher's question, the user behavior data to be collected may be the user's gesture data to determine whether the user takes hands in response to the teacher's question. Still further, other types of user behavior data may be suspended from collection to conserve resources. For another example, when the content type of the first video data is a teacher roll call, the user behavior data to be collected may be user voice data to determine whether the corresponding user answers the teacher roll call. Also, other types of user behavior data may be suspended from collection to conserve resources.
For example, the environmental data of the place where the user is located may be collected periodically, or when the content of the first video data relates to causing a plurality of persons to answer a question. By adjusting the collected user behavior data in coordination with the played video data, the accurate feedback of the user on the course content can be more accurately obtained, the efficiency of video playing is improved, and the user experience is further improved.
With continued reference to fig. 2, a candidate set including candidate video data to be provided after the start of playing the first video data is obtained at block 220. In the system architecture 100 shown in fig. 1, the operations shown in block 220 may be implemented in the decision processor 102. However, those skilled in the art will appreciate that the system architecture 100 shown in FIG. 1 is merely exemplary, and that the steps may well be implemented with other existing or yet to be added modules in an implementation. Each piece of candidate video data in the candidate set is associated in content with the first video data, which may be played after the first video data is played or during the playing of the first video data. It is noted that, whether played during or after the playing of the first video data, the video data switch is not perceived by the user as the candidate video data is associated in content with the first video data, in this way it is ensured that the video switch is transparent to the user.
In some embodiments, the candidate set may be obtained from a profile of the first video data. Fig. 3 illustrates an exemplary block diagram of a profile 300 for video data according to an embodiment of the disclosure. As shown in fig. 3, in some embodiments, each piece of video data has its own profile. For example, profiles 300 may include a profile 310 for video 1, a profile 320 for video 2, and so on. The profiles are similar in format, and the profile 310 of video 1 is described as an example.
In some embodiments, the configuration file 310 for video 1 may include, for example:
1. video ID of video 1 itself;
2. video address/URL of video 1;
3. candidate video set names to be provided after video 1;
4. a video data selector name for scheduling video 1;
……
after determining that video 1 is to be played, before starting to play video 1, the decision processor 102 shown in fig. 1, for example, obtains a configuration file for video 1 by the video ID of video 1. The decision processor 102 may find the video address or URL of the video 1 from the configuration file in order to obtain the video content data of the video 1.
In a further embodiment, the profile 310 also includes a video data selector name for scheduling video 1, which is used to limit video 1 to be played only when scheduled by the video data selector. As described with reference to fig. 1, the video data selector 103 is configured to select corresponding video data from a plurality of video data and finally play the selected video data 160 played to the user. In this further embodiment, there may be a plurality of video data selectors 103 for invoking different kinds of video data. Erroneous invocation of video data can be prevented by defining which video data selectors 103 the video data can be invoked.
Those skilled in the art will appreciate that configuration file 310 may also include other content as desired, and the content of configuration file 310 listed in FIG. 4 is not intended to be limiting.
In addition, the decision processor 102 shown in fig. 1 also obtains the candidate video set name to be provided after video 1 from the configuration file 310, and selects the video played after video 1 is played from the candidate video set name based on the specific situation.
Returning to method 200. At block 230, second video data to be played to the user is determined from the candidate set based on the collected behavior data. There are various data provided after the first video data starts playing. In some embodiments, the obtained candidate set includes regular video data indicating video data to be played to the user after playing the first video data and spot video data indicating video data to be played to the user during playing of the first video data. Both the regular video data and the break-in video data may be played as second video data.
It should also be understood by those skilled in the art that the "second video data" is merely for convenience of description, is distinguished from the "first video data" in name, and does not constitute a specific limitation on video content. In a specific implementation, when the first video data is completely played and the second video data starts to be played, the second video data can be completely used as new "first video data" to repeat the playing process described above and below for the "first video data".
The playing of regular video data and break-in video data is further described with reference to fig. 4. Referring to fig. 4, a flow diagram of a further method 400 for playing video data to a user is shown, in accordance with an embodiment of the present disclosure.
At block 410, it is determined whether there is predetermined behavior data in the collected behavior data, and when the determination is yes, the method 400 proceeds to block 420 to select spot video data from the candidate set that matches the predetermined behavior data.
As described above, the behavior data of the user may include facial expressions, body gestures, voice, environment data, etc. of the user, which reflect the user's class state. Therefore, the user can know the user's listening situation in real time from the user's behavior data, so that the user can respond to the user's classroom behavior in time. Correspondingly, the course experience of the user can be improved by prescribing the preset behavior data in advance and triggering the corresponding classroom corresponding mode when the behavior data of the user meets the preset behavior data.
For example, the predetermined behavioral data may include the user sleeping in a classroom or the user walking around a classroom. When these predetermined behavioural data occur, the decision processor 102 may be triggered via the trigger 101 shown in fig. 1 to play the corresponding spot video data during the play of the first video data. For example, the video data of the break may be video content that a teacher reminds of the classroom discipline and stops his/her behavior.
As another example, the predetermined behavioral data may also include the user actively taking hands in a classroom to ask a teacher for questions. When such predetermined behavior data occurs, then one of the following spot videos may be played during the playing of the first video data: the teacher agrees to the students who raise hands to raise standing questions; or the teacher explicitly indicates that questions are not currently allowed to be asked and that questions are to be answered in unison after the course is over.
It should be understood that the above predetermined behavior data is merely exemplary and not exhaustive. Other behavior data which need to be triggered to deal with the video insertion data can be defined according to needs and associated with the corresponding video insertion data. Embodiments of the present disclosure are not limited in this respect. The inter-cut video data played during the first video playing period is specially designed, so that the emergency in a classroom can be dealt with in time, the active interaction of students is processed, the enthusiasm of the students is improved, and the video playing efficiency is improved.
At block 420, in some embodiments, the method 400 may further proceed to block 430 to confirm whether the break-in video data has already been played to the user, and upon determining that it has already been played, the method 400 proceeds to block 440 to continue playing the unplayed portion of the first video data to the user.
It is to be readily understood that after the response to the predetermined behavior data ends, the unplayed portion of the first video data may continue to be played to the user to complete the playing of the lesson video.
Returning to block 410 of the method 400, when it is determined that the predetermined behavior data does not exist in the collected behavior data, the method 400 proceeds to block 450 to select regular video data from the candidate set. As described above, the regular video data indicates video data to be played to the user after the first video data is played. It should be noted that, at this time, one or more conventional video data may be played to the user after the first video data. In the case where there are a plurality of regular video data, there is still a need to select one regular video data from the plurality of regular video data based on the behavior data of the user.
For example, in some embodiments, the content of the first video data may include a teacher's explanation of the course. In this scenario, at the end of the first video playback, different subsequent regular video data may be invoked depending on the student behavior data. For example, when the student has pleasant facial expressions and a loud voice, the student may consider that the student has no question about the content of the first video data that has just been played by analyzing the student behavior data (facial expressions, voice, etc.), and the decision processor 102 selects a corresponding next video file to be played from the regular video data according to the behavior data to accept the first video for playing, where the next video file to be played may be a new course in content; when the facial expressions of the students are confused and the voices are disordered, the students can be considered to have no understanding and doubtful about the content of the first video data which is just played by analyzing the student behavior data (the facial expressions, the voice and other data). The decision processor 102 selects a corresponding next video file to be played from the regular video data according to the behavior data to be played after receiving the first video, and the content of the next video file to be played at this time may be detailed again for the current student confusion, so as to deeply adjust the learning progress and state of the student.
It will be appreciated by those skilled in the art that when the content of the first video data comprises interactive content with a student, it is often the case that different subsequent regular video data will be invoked depending on the result of different interactions with the student. At this point, a selection may be made from a plurality of subsequent regular video data based on the collected behavioral data of the user.
Different responses can be given to different interaction results of the user by playing a plurality of possible candidate conventional video data after the first video data, so that the video is flexibly played to the user according to the user condition on the basis of ensuring the video continuity, and the experience of the user participating in the course is further improved besides the improvement of the flexibility of video playing.
Returning to method 200, after determining the second video data to be played to the user, method 200 proceeds to block 240 to play the second video data to the user, thereby ensuring that the first video data, the second video data appear to the user as a continuous video clip over the content. It should be understood by those skilled in the art that after the video data is divided into a plurality of video data segments, the video data segments can be flexibly scheduled through, for example, blocks 210 to 240 shown in the method 200, so that on one hand, the video segments with content continuity can be guaranteed to be played to the user, and on the other hand, the interaction of the user is fully considered in the video playing process, so as to bring a good experience to the user.
In some embodiments, the data played in association with the first video data may include additional data associated with the first video data in addition to the aforementioned content of the break-in video data and the regular video data as part of the lesson content. These additional data each have a corresponding trigger condition, which when satisfied, can be invoked by the decision processor 102 shown in fig. 1 and provide the corresponding additional data to the user. In some embodiments, the additional data may include at least any one of picture data, animation data, projection data, voice data, and interactive component data for interacting with a user.
Specifically, during the playing of the first video data, for example, a teacher may be explaining the physical structure of the dinosaur, and at this time, picture data of the dinosaur or animation data of the dinosaur, or even projection data of the dinosaur, which is additional data, may be played simultaneously with the corresponding content of the first video data, facilitating the user to better understand the course content. In addition, the sound of the dinosaur can be played in a classroom in a voice data mode, so that the user has more realistic experience.
In other embodiments, the user may also be provided with interactive component data that interacts with the interaction during playback of the first video. The interactive component data can be used to provide an interactive interface to the user in anticipation of the user providing interactive input, such as a red envelope dispatch function, or to initiate a user answer interface, among others.
By providing additional data besides conventional course video data, the teaching effect of video teaching can be improved, the video data can be played more efficiently, and the user experience is further improved.
In a further embodiment, the trigger condition for the additional data may comprise a trigger time for providing the additional data. It will be appreciated by those skilled in the art that the trigger time is only one instance of a trigger condition and that other trigger conditions (e.g., meeting a predetermined condition, i.e., triggering, etc.) are equally applicable to the additional data. In addition, the trigger time may be an absolute time for providing the additional data, or may be a relative time with respect to a start point of the first video data, or a relative time with respect to an end point of the first video data, and embodiments of the present disclosure are not limited herein.
By defining the trigger condition for the additional data separately to determine whether to trigger the additional data, flexibility can be further increased for playing the video data, and a more flexible experience of watching the video is brought to the user.
An exemplary block diagram of a profile 500 of additional data according to an embodiment of the present disclosure is described below with reference to fig. 5. As shown in FIG. 5, in some embodiments, each additional data has its own configuration file. For example, configuration file 500 may include configuration file 510 for additional data 1, configuration file 520 for additional data 2, and so on. The configuration file formats are similar, and the configuration file 510 to which data 1 is added will be described below as an example.
In some embodiments, configuration file 510 may include, for example:
1. video ID of the additional data 1 itself;
2. the trigger time of the additional data 1;
3. the trigger type of the additional data 1;
4. video ID associated with the additional data 1;
5. a required AI model;
……
similar to the profile 310, after determining that video 1 is to be played and before starting to play video 1, the decision processor 102 shown in fig. 1, for example, also obtains the additional data ID and its profile associated therewith from the video ID of video 1. Next, based on the profile, for example, the decision processor 102 periodically (e.g., every minute, every second, etc.) polls for satisfaction of a trigger time for additional data associated with video 1. And when the trigger time is up, triggering according to the trigger type of the additional data, wherein the trigger is triggered after the video 1 starts to play or after the video 1 finishes playing.
In addition, as previously described, depending on the specifics of the additional data, its profile may also include information on which AI models are needed for the additional data to assist in processing the collected user audio and video data. For example, when the additional data 1 is user speech data, it may be expected that the user also has corresponding speech feedback, so that it may be required to start the speech analysis AI model at this stage to ensure that the speech data in the user behavior data is provided to the decision processor 102 shown in fig. 1, for example.
It will also be appreciated by those skilled in the art that the configuration file 510 may also include other content as desired, and that the contents of the configuration file 510 listed in FIG. 5 are not to be construed as limiting thereof.
The above describes a scheme for playing video data to a user in conjunction with fig. 1 to 5. By the scheme, the video clip to be played next can be continuously adjusted according to the behavior data of the user watching the video data, so that the played content is associated with the behavior of the user as much as possible, the effect of playing the video data to the user is improved, and the watching experience of the user is also improved.
In some embodiments, an apparatus for playing video data to a user is provided. Fig. 6 shows a block diagram of an apparatus 600 for playing video data to a user according to an embodiment of the present disclosure. The apparatus 600 comprises: a collecting module 610 configured to collect behavior data of a user during playing of the first video data to the user; an obtaining module 620 configured to obtain a candidate set including candidate video data to be provided after starting to play the first video data; a determining module 630 configured to determine second video data to be played to the user from the candidate set based on the behavior data; and a providing module 640 configured to play the second video data to the user.
In some embodiments, the candidate set includes regular video data and spot video data, the regular video data indicating video data to be played to the user after the first video data is played, and the spot video data indicating video data to be played to the user during the playing of the first video data; and the determining module 630 is further configured to include: in response to determining that predetermined behavioural data is present in the behavioural data, selecting cut-in video data from the candidate set that matches the predetermined behavioural data; and selecting regular video data from the candidate set in response to determining that the predetermined behavior data does not exist in the behavior data.
In some embodiments, the providing module 640 is further configured to: in response to determining that the spot video data has been played to the user, the unplayed portion of the first video data continues to be played to the user.
In some embodiments, further comprising: an additional data determination module configured to determine additional data associated with the first video data; and an additional data providing module configured to provide the additional data to the user in response to a trigger condition of the additional data being satisfied.
In some embodiments, the trigger condition includes a trigger time for providing the additional data.
In some embodiments, the trigger time comprises at least one of an absolute time for providing the additional data, a relative time with respect to a start point of the first video data, and an end point time with respect to the first video data.
In some embodiments, the additional data comprises at least any one of the following types: picture data, animation data, projection data, voice data, and interactive component data for interacting with a user.
In some embodiments, the behavioral data includes at least any one of the following categories: expression data, posture data, voice data of the user and environment data of the place where the user is located.
In some embodiments, the collection module is further configured to: behavior data of the user to be collected is determined based on the content type of the first video data.
FIG. 7 schematically illustrates a block diagram of an electronic device 700 suitable for use in implementing embodiments of the present disclosure. Device 700 may be used to implement methods 200 and 400 for playing video data to a user as illustrated in fig. 2 and 3. As shown in fig. 7, device 700 includes a Central Processing Unit (CPU)701 that may perform various appropriate actions and processes in accordance with computer program instructions stored in a Read Only Memory (ROM)702 or computer program instructions loaded from a storage unit 708 into a Random Access Memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the device 700 can also be stored. The CPU 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.
Various components in the device 700 are connected to the I/O interface 705, including: an input unit 706 such as a keyboard, a mouse, or the like; an output unit 707 such as various types of displays, speakers, and the like; a storage unit 708 such as a disk, an optical disk, or the like; and a communication unit 709 such as a network card, modem, wireless communication transceiver, etc. The communication unit 709 allows the device 700 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
The processing unit 701 performs the various methods and processes described above, such as performing the method 200 and/or the method 400 for playing video data to a user. For example, in some embodiments, method 200 and/or method 400 may be implemented as a computer software program stored on a machine-readable medium, such as storage unit 708. In some embodiments, part or all of a computer program may be loaded onto and/or installed onto device 700 via ROM 702 and/or communications unit 709. When the computer program is loaded into the RAM 703 and executed by the CPU 701, one or more operations of the methods 200 or 400 described above may be performed. Alternatively, in other embodiments, CPU 701 may be configured by any other suitable means (e.g., by way of firmware) to perform one or more acts of method 200 and/or method 400.
It should be further appreciated that the present disclosure may be embodied as methods, apparatus, systems, and/or computer program products. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied thereon for carrying out various aspects of the present disclosure.
The computer readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but is not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.
The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device via a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.
The computer program instructions for carrying out operations of the present disclosure may be assembler instructions, Instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, the electronic circuitry that can execute the computer-readable program instructions implements aspects of the present disclosure by utilizing the state information of the computer-readable program instructions to personalize the electronic circuitry, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA).
Various aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.
These computer-readable program instructions may be provided to a processing unit of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processing unit of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Having described embodiments of the present disclosure, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
The above are merely alternative embodiments of the present disclosure and are not intended to limit the present disclosure, which may be modified and varied by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present disclosure should be included in the protection scope of the present disclosure.
Claims (18)
1. A method for playing video data to a user, comprising:
during the playing of first video data to a user, collecting behavior data of the user;
obtaining a candidate set including candidate video data to be provided after starting to play the first video data;
determining second video data to be played to the user from the candidate set based on the behavior data; and
playing the second video data to the user;
wherein determining the second video data comprises:
in response to determining that predetermined behavioural data is present in the behavioural data, selecting, from the candidate set, break-in video data that matches the predetermined behavioural data as the second video data, the break-in video data indicating video data to be played to the user during playback of the first video data;
wherein the candidate set further comprises regular video data indicating video data to be played to the user after playing the first video data;
wherein determining the second video data further comprises:
in response to determining that the predetermined behavior data is not present in the behavior data, selecting regular video data from the candidate set as the second video data based on the behavior data.
2. The method of claim 1, further comprising:
in response to determining that the spot video data has been played to the user, continuing to play the unplayed portion of the first video data to the user.
3. The method of claim 1, further comprising:
determining additional data associated with the first video data; and
providing the additional data to the user in response to a trigger condition for the additional data being satisfied.
4. The method of claim 3, wherein the trigger condition comprises a trigger time for providing the additional data.
5. The method of claim 4, wherein the trigger time comprises at least one of an absolute time for providing the additional data, a relative time with respect to a starting point of the first video data, and an ending point time with respect to the first video data.
6. The method of claim 5, wherein the additional data comprises at least any one of the following types: picture data, animation data, projection data, voice data, and interactive component data for interacting with the user.
7. The method of claim 1, wherein the behavioral data comprises at least any one of the following categories: the expression data, the posture data and the voice data of the user and the environment data of the place where the user is located.
8. The method of claim 1, further comprising:
determining behavior data of the user to be collected based on a content type of the first video data.
9. An apparatus for playing video data to a user, comprising:
a collection module configured to collect behavior data of a user during a playback of first video data to the user;
an acquisition module configured to acquire a candidate set including candidate video data to be provided after starting playing of the first video data;
a determination module configured to determine second video data to be played to the user from the candidate set based on the behavior data; and
a providing module configured to play the second video data to the user;
wherein the determining module is further configured to:
in response to determining that predetermined behavioural data is present in the behavioural data, selecting, from the candidate set, break-in video data that matches the predetermined behavioural data as the second video data, the break-in video data indicating video data to be played to the user during playback of the first video data;
wherein the candidate set further comprises regular video data indicating video data to be played to the user after playing the first video data;
wherein the determining module is further configured to:
in response to determining that the predetermined behavior data is not present in the behavior data, selecting regular video data from the candidate set as the second video data based on the behavior data.
10. The apparatus of claim 9, the providing module further configured to:
in response to determining that the spot video data has been played to the user, continuing to play the unplayed portion of the first video data to the user.
11. The apparatus of claim 9, further comprising:
an additional data determination module configured to determine additional data associated with the first video data; and
an additional data providing module configured to provide the additional data to the user in response to a trigger condition of the additional data being satisfied.
12. The apparatus of claim 11, wherein the trigger condition comprises a trigger time for providing the additional data.
13. The apparatus of claim 12, wherein the trigger time comprises at least one of an absolute time for providing the additional data, a relative time with respect to a starting point of the first video data, and an ending point time with respect to the first video data.
14. The apparatus of claim 13, wherein the additional data comprises at least any one of the following types: picture data, animation data, projection data, voice data, and interactive component data for interacting with the user.
15. The apparatus of claim 9, wherein the behavior data comprises at least any one of the following categories: the expression data, the posture data and the voice data of the user and the environment data of the place where the user is located.
16. The apparatus of claim 9, the collection module further configured to:
determining behavior data of the user to be collected based on a content type of the first video data.
17. An apparatus, the apparatus comprising:
one or more processors; and
storage means for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to carry out the method according to any one of claims 1 to 8.
18. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 8.
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