WO2023062794A1

WO2023062794A1 - Video meeting evaluation terminal

Info

Publication number: WO2023062794A1
Application number: PCT/JP2021/038123
Authority: WO
Inventors: 渉三神谷
Original assignee: 株式会社I’mbesideyou
Priority date: 2021-10-14
Filing date: 2021-10-14
Publication date: 2023-04-20
Also published as: JPWO2023062794A1; JP7197955B1

Abstract

[Problem] To objectively evaluate communication under circumstances in which online communications have become mainstream. [Solution] A video analysis system of the present disclosure analyzes user reactions on the basis of a video obtained by videoing users, regardless of whether users are displayed on a screen during a video meeting in an environment in which a video meeting is conducted by a plurality of users, said system comprising: a video acquisition unit that acquires video obtained by videoing the users during a video meeting; a participant analysis unit that analyzes the acquired video to identify participants; and a statistical information generation unit that generates statistical information including at least information regarding the users and participants conducting the video meeting.

Description

Video meeting evaluation terminal

The present invention relates to a video meeting evaluation terminal that analyzes the biological reactions of participants based on moving images obtained from online sessions conducted by multiple participants.

A technique is known for analyzing the emotions others receive in response to a speaker's remarks (see Patent Document 1, for example). There is also known a technique for chronologically analyzing changes in a subject's facial expression over a long period of time and estimating the emotions held during that period (see Patent Document 2, for example). There are also known techniques for identifying the factors that most affected changes in emotions (see Patent Documents 3 to 5, for example). There is also known a technique that compares the subject's usual facial expression with the current facial expression and issues an alert when the facial expression is dark (see Patent Document 6, for example). There is also known a technique for determining the degree of emotion of a subject by comparing the subject's normal (expressionless) facial expression with the current facial expression (see, for example, Patent Documents 7 to 9). . Techniques for analyzing the emotions of an organization and the atmosphere felt by individuals within a group are also known (see

Patent Documents

10 and 11, for example).

JP 2019-58625 A JP 2016-149063 A JP 2020-86559 A JP-A-2000-76421 JP 2017-201499 A JP 2018-112831 A JP 2011-154665 A JP-A-2012-8949 Japanese Unexamined Patent Application Publication No. 2013-300 JP 2011-186521 A WO15/174426

All the technologies mentioned above are only sub-functions in situations where communication in the real world is the main thing. In other words, due to the recent DX (Digital Transformation) of work and the global epidemic of infectious diseases, it is not a situation where communication such as work and classes is mainly conducted online.

The purpose of the present invention is to objectively evaluate these communications in order to conduct more efficient communication in situations where online communication is the main focus, such as meetings and lectures.

According to the invention,
In an environment where a video meeting is held with a plurality of users, the reaction of the user is analyzed based on the moving image obtained by shooting the user regardless of whether or not the user is displayed on the screen during the video meeting. A moving image analysis system for
a moving image acquisition unit that acquires a moving image obtained by shooting the user during the video meeting;
a participant analysis unit that analyzes the acquired moving image to identify participants;
a statistical information generating unit that generates statistical information including at least information of the participants who have had the video meeting with the user;
A video meeting evaluation terminal is provided.

According to the present disclosure, by analyzing and evaluating moving images of a video session, it is possible to objectively evaluate especially the content.

It is a figure which shows the whole system diagram by embodiment of this invention. 1 is an example of a functional block diagram of an evaluation terminal according to an embodiment of the present invention; FIG. FIG. 3 is a diagram showing functional configuration example 1 of the evaluation terminal according to the embodiment of the present invention; FIG. 8 is a diagram showing functional configuration example 2 of the evaluation terminal according to the embodiment of the present invention; FIG. 10 is a diagram showing a functional configuration example 3 of the evaluation terminal according to the embodiment of the present invention; 7 is a screen display example according to the functional configuration example 3 of FIG. 6. FIG. FIG. 7 is another screen display example according to the functional configuration example 3 of FIG. 6. FIG. FIG. 12 is a diagram showing another configuration of functional configuration example 3 of the evaluation terminal according to the embodiment of the present invention; FIG. 12 is a diagram showing another configuration of functional configuration example 3 of the evaluation terminal according to the embodiment of the present invention; It is a figure which shows the structure of the statistical information production|generation part by embodiment of this invention.

The contents of the embodiments of the present disclosure are listed and described. The present disclosure has the following configurations.
[Item 1]
In an environment where a video meeting is held with a plurality of users, the reaction of the user is analyzed based on the moving image obtained by shooting the user regardless of whether or not the user is displayed on the screen during the video meeting. A moving image analysis system for
a moving image acquisition unit that acquires a moving image obtained by shooting the user during the video meeting;
a participant analysis unit that analyzes the acquired moving image to identify participants;
a statistical information generating unit that generates statistical information including at least information of the participants who have had the video meeting with the user;
Video meeting evaluation terminal.
[Item 2]
The video meeting evaluation terminal according to item 1,
an analysis unit that analyzes changes in biological reactions of the user based on the moving image acquired by the moving image acquisition unit;
A providing unit that provides the result of the analysis to the user,
Video meeting evaluation terminal.
[Item 3]
The video meeting evaluation terminal according to item 2,
The statistical information generation unit generates statistical information about compatibility between the user and the participant based on the results of analyzing changes in the biological reactions of both the user and the participant.
Video meeting evaluation terminal.
[Item 4]
A video meeting evaluation terminal according to item 2 or item 3,
The participant analysis unit identifies a name by recognizing the face included in the acquired moving image and referring to information stored in advance based on each face.
Video meeting evaluation terminal.
[Item 5]
A video meeting evaluation terminal according to any one of items 2 to 4,
The statistical information generation unit includes at least one of meeting time of users and participants in the video meeting, speech time of each, speech frequency, order of speech, and words spoken,
Video meeting evaluation terminal.
[Item 6]
The video meeting evaluation terminal according to any one of items 2 to 5,
The statistical information generator generates information about changes in current and past statistical information of the user and the participant.
Video meeting evaluation terminal.
[Item 7]
The video meeting evaluation terminal according to item 1,
further comprising an emotion evaluation unit that evaluates the degree of emotion of the user according to an evaluation criterion leveled among a plurality of users based on changes in the biological reaction;
The emotion evaluation unit determines the degree of emotion based on the magnitude of the difference between the current biological reaction and the normal biological reaction, and the degree of emotion adjusted according to the likelihood of the same emotion occurring by the user. evaluate,
Video meeting evaluation terminal.
[Item 8]
The video meeting evaluation terminal according to item 1,
whether or not the change in the biological reaction analyzed for the user with respect to one video meeting is specific compared to the change in the biological reaction analyzed for the user with respect to the video meeting temporally earlier than the one video meeting; determining and clustering the patterns of changes in biological responses based on the content of the changes in biological responses determined to be specific and the magnitude of the change from before;
Video meeting evaluation terminal.
[Item 9]
The video meeting evaluation terminal according to item 1,
Analyzing the movement of the eyes of each of the plurality of users to generate a heat map indicating the direction of the eyes, and analyzing the user by comparing the generated heat map with the heat maps generated for other users A determination unit that determines whether the change in the biological reaction obtained is specific compared to the change in the biological reaction analyzed for the other user,
Video meeting evaluation terminal.
[Item 10]
The video meeting evaluation terminal according to item 1,
Determining whether the change in the biological reaction analyzed for the user is specific compared to the change in the biological reaction analyzed for another user, and the biological reaction determined to be specific to the user identifying an event occurring with respect to at least one of the user, the other user, or the environment when a change occurs in the user, and analyzing the degree of correlation between the change in the user's biological reaction and the event , clustering the user or the event based on the analysis result of the correlation when it is determined that the correlation is equal to or higher than a certain level;
Video meeting evaluation terminal.

Preferred embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. In the present specification and drawings, constituent elements having substantially the same functional configuration are denoted by the same reference numerals, thereby omitting redundant description.

<Basic functions>
In the video session evaluation system of the present embodiment, in an environment where a video session (hereinafter referred to as an online session including one-way and two-way sessions) is held by a plurality of people, the person to be analyzed among the plurality of people is different from the others. It is a system that analyzes and evaluates specific emotions (feelings that occur in response to one's own or others' words and actions. Pleasant/unpleasant, or their degree). Online sessions are, for example, online meetings, online classes, online chats, etc. Terminals installed in multiple locations are connected to a server via a communication network such as the Internet, and moving images are transmitted between multiple terminals through the server. It's made to be interactable. Moving images handled in online sessions include facial images and voices of users using terminals. Moving images also include images such as materials that are shared and viewed by a plurality of users. It is possible to switch between the face image and the document image on the screen of each terminal to display only one of them, or to divide the display area and display the face image and the document image at the same time. In addition, it is possible to display the image of one user out of a plurality of users on the full screen, or divide the images of some or all of the users into small screens and display them. It is possible to designate one or a plurality of users among a plurality of users participating in an online session using terminals as analysis subjects. For example, an online session leader, moderator, or manager (hereinafter collectively referred to as the organizer) designates any user as an analysis subject. Hosts of online sessions are, for example, instructors of online classes, chairpersons and facilitators of online meetings, coaches of sessions for coaching purposes, and the like. An online session host is typically one of the users participating in the online session, but may be another person who does not participate in the online session. It should be noted that all participants may be subject to analysis without specifying the person to be analyzed. In addition, it is also possible for an online session leader, moderator, or administrator (hereinafter collectively referred to as the organizer) to designate any user as an analysis subject. Hosts of online sessions are, for example, instructors of online classes, chairpersons and facilitators of online meetings, coaches of sessions for coaching purposes, and the like. An online session host is typically one of the users participating in the online session, but may be another person who does not participate in the online session.

The video session evaluation system according to the present embodiment displays at least moving images obtained from a video session established between a plurality of terminals. The displayed moving image is acquired by the terminal, and at least a face image included in the moving image is identified for each predetermined frame unit. An evaluation value for the identified face image is then calculated. The evaluation value is shared as necessary. In particular, in this embodiment, the acquired moving image is stored in the terminal, analyzed and evaluated on the terminal, and the result is provided to the user of the terminal. Therefore, for example, even a video session containing personal information or a video session containing confidential information can be analyzed and evaluated without providing the moving image itself to an external evaluation agency or the like. In addition, by providing only the evaluation result (evaluation value) to the external terminal as necessary, the result can be visualized and cross-analysis can be performed.

As shown in FIG. 1, the video session evaluation system according to the present embodiment includes

user terminals

10 and 20 each having at least an input unit such as a camera unit and a microphone unit, a display unit such as a display, and an output unit such as a speaker. , a video session service terminal 30 for providing an interactive video session to the

user terminals

10, 20, and an evaluation terminal 40 for performing part of the evaluation of the video session.

<Hardware configuration example>
Each functional block, functional unit, and functional module described below can be configured by any of hardware, DSP (Digital Signal Processor), and software provided in a computer, for example. For example, when configured by software, it is actually configured with a computer CPU, RAM, ROM, etc., and is realized by running a program stored in a recording medium such as RAM, ROM, hard disk, or semiconductor memory. A series of processes by the systems and terminals described herein may be implemented using software, hardware, or a combination of software and hardware. It is possible to prepare a computer program for realizing each function of the user terminal 10 according to the present embodiment and to implement it in a PC or the like. It is also possible to provide a computer-readable recording medium storing such a computer program. The recording medium is, for example, a magnetic disk, an optical disk, a magneto-optical disk, a flash memory, or the like. Also, the above computer program may be distributed, for example, via a network without using a recording medium.

The evaluation terminal according to the present embodiment acquires a moving image from a video session service terminal, identifies at least a face image included in the moving image for each predetermined frame unit, and calculates an evaluation value for the face image ( will be described in detail later).

<How to get videos>
As shown in FIG. 2, the video session service provided by the video session service terminal (hereinafter sometimes simply referred to as "this service") provides

user terminals

10 and 20 with two-way images and voice. Communication is possible. In this service, a moving image captured by the camera of the other user's terminal is displayed on the display of the user's terminal, and audio captured by the microphone of the other's user's terminal can be output from the speaker. In addition, this service allows both or either of the user terminals to record moving images and sounds (collectively referred to as "moving images, etc.") in the storage unit of at least one of the user terminals. configured as possible. The recorded moving image information Vs (hereinafter referred to as “recorded information”) is cached in the user terminal that started recording and is locally recorded only in one of the user terminals. If necessary, the user can view the recorded information by himself or share it with others within the scope of using this service.

<Functional configuration example 1>
FIG. 3 is a block diagram showing a configuration example according to this embodiment. As shown in FIG. 3, the video session evaluation system of this embodiment is implemented as a functional configuration of the user terminal 10. FIG. That is, the user terminal 10 has, as its functions, a moving image acquisition unit 11, a biological reaction analysis unit 12, a peculiar determination unit 13, a related event identification unit 14, a clustering unit 15, and an analysis result notification unit 16.

The moving image acquisition unit 11 acquires from each terminal a moving image obtained by photographing a plurality of people (a plurality of users) with a camera provided in each terminal during an online session. It does not matter whether the moving image acquired from each terminal is set to be displayed on the screen of each terminal. That is, the moving image acquisition unit 11 acquires moving images from each terminal, including moving images being displayed and moving images not being displayed on each terminal.

The biological reaction analysis unit 12 analyzes changes in the biological reaction of each of a plurality of people based on the moving images (whether or not they are being displayed on the screen) acquired by the moving image acquiring unit 11. In the present embodiment, the biological reaction analysis unit 12 separates the moving image acquired by the moving image acquisition unit 11 into a set of images (collection of frame images) and voice, and analyzes changes in the biological reaction from each.

For example, the biological reaction analysis unit 12 analyzes the user's facial image using a frame image separated from the moving image acquired by the moving image acquisition unit 11 to obtain at least one of facial expression, gaze, pulse, and facial movement. Analyze changes in biological reactions related to Further, the biological reaction analysis unit 12 analyzes the voice separated from the moving image acquired by the moving image acquisition unit 11 to analyze changes in the biological reaction related to at least one of the user's utterance content and voice quality.

When a person's emotions change, it manifests as a change in biological reactions such as facial expressions, eye gaze, pulse, facial movements, content of remarks, and voice quality. In this embodiment, changes in the user's emotions are analyzed through analysis of changes in the user's biological reactions. The emotion analyzed in this embodiment is, for example, the degree of comfort/discomfort. In the present embodiment, the biological reaction analysis unit 12 calculates a biological reaction index value reflecting the change in biological reaction by quantifying the change in biological reaction according to a predetermined standard.

For example, the analysis of changes in facial expressions is performed as follows. That is, for each frame image, a facial region is identified from the frame image, and the identified facial expressions are classified into a plurality of types according to an image analysis model machine-learned in advance. Then, based on the classification results, it analyzes whether positive facial expression changes occur between consecutive frame images, whether negative facial expression changes occur, and to what extent the facial expression changes occur, A facial expression change index value corresponding to the analysis result is output.

For example, the analysis of changes in line of sight is performed as follows. That is, for each frame image, the eye region is specified in the frame image, and the orientation of both eyes is analyzed to analyze where the user is looking. For example, it analyzes whether the user is looking at the face of the speaker being displayed, whether the user is looking at the shared material being displayed, or whether the user is looking outside the screen. Also, it may be analyzed whether the eye movement is large or small, or whether the movement is frequent or infrequent. A change in line of sight is also related to the user's degree of concentration. The biological reaction analysis unit 12 outputs a line-of-sight change index value according to the analysis result of the line-of-sight change.

The analysis of pulse changes is performed, for example, as follows. That is, for each frame image, the face area is specified in the frame image. Then, using a trained image analysis model that captures numerical values of face color information (G of RGB), changes in the G color of the face surface are analyzed. By arranging the results along the time axis, a waveform representing changes in color information is formed, and the pulse is identified from this waveform. When a person is tense, the pulse speeds up, and when the person is calm, the pulse slows down. The biological reaction analysis unit 12 outputs a pulse change index value according to the analysis result of the pulse change.

For example, analysis of changes in facial movement is performed as follows. That is, for each frame image, the face area is specified in the frame image, and the direction of the face is analyzed to analyze where the user is looking. For example, it analyzes whether the user is looking at the face of the speaker being displayed, whether the user is looking at the shared material being displayed, or whether the user is looking outside the screen. Further, it may be analyzed whether the movement of the face is large or small, or whether the movement is frequent or infrequent. The movement of the face and the movement of the line of sight may be analyzed together. For example, it may be analyzed whether the face of the speaker being displayed is viewed straight, whether the face is viewed with upward or downward gaze, or whether the face is viewed obliquely. The biological reaction analysis unit 12 outputs a face orientation change index value according to the analysis result of the face orientation change.

　Analysis of the contents of the statement is performed, for example, as follows. That is, the biological reaction analysis unit 12 converts the voice into a character string by performing known voice recognition processing on the voice for a specified time (for example, about 30 to 150 seconds), and morphologically analyzes the character string. By doing so, words such as particles and articles that are unnecessary for expressing conversation are removed. Then, vectorize the remaining words, analyze whether a positive emotional change has occurred, whether a negative emotional change has occurred, and to what extent the emotional change has occurred. Outputs the utterance content index value.

Voice quality analysis is performed, for example, as follows. That is, the biological reaction analysis unit 12 identifies the acoustic features of the voice by performing known voice analysis processing on the voice for a specified time (for example, about 30 to 150 seconds). Then, based on the acoustic features, it analyzes whether a positive change in voice quality has occurred, whether a negative change in voice quality has occurred, and to what extent the change in voice quality has occurred, and according to the analysis results, output the voice quality change index value.

The biological reaction analysis unit 12 uses at least one of the facial expression change index value, eye line change index value, pulse change index value, face direction change index value, statement content index value, and voice quality change index value calculated as described above. to calculate the biological reaction index value. For example, the biological reaction index value is calculated by weighting the facial expression change index value, eye line change index value, pulse change index value, face direction change index value, statement content index value, and voice quality change index value.

The peculiarity determination unit 13 determines whether or not the change in the analyzed biological reaction of the person to be analyzed is more specific than the change in the analyzed biological reaction of the person other than the person to be analyzed. In the present embodiment, the peculiarity determination unit 13 compares changes in the biological reaction of the person to be analyzed with those of others based on the biological reaction index values calculated for each of the plurality of users by the biological reaction analysis unit 12. is specific or not.

For example, the peculiar determination unit 13 calculates the variance of the biological reaction index values calculated for each of the plurality of persons by the biological reaction analysis unit 12, and compares the biological reaction index values calculated for the analysis subject with the variance, It is determined whether or not the change in the analyzed biological reaction of the person to be analyzed is specific compared to others.

The following three patterns are conceivable as cases where the changes in biological reactions analyzed for the subject of analysis are more specific than those of others. The first is a case where a relatively large change in biological reaction occurs in the subject of analysis, although no particularly large change in biological reaction has occurred in the other person. The second is a case where a particularly large change in biological reaction has not occurred in the subject of analysis, but a relatively large change in biological reaction has occurred in the other person. The third is a case where a relatively large change in biological reaction occurs in both the subject of analysis and the other person, but the content of the change differs between the subject of analysis and the other person.

The related event identification unit 14 identifies an event occurring in relation to at least one of the person to be analyzed, the other person, and the environment when the change in the biological reaction determined to be peculiar by the peculiarity determination unit 13 occurs. . For example, the related event identification unit 14 identifies from the moving image the speech and behavior of the person to be analyzed when a specific change in biological reaction occurs in the person to be analyzed. In addition, the related event identifying unit 14 identifies, from the moving image, the speech and behavior of the other person when a specific change in the biological reaction of the person to be analyzed occurs. In addition, the related event identification unit 14 identifies from the moving image the environment in which a specific change in the biological reaction of the person to be analyzed occurs. The environment is, for example, the shared material being displayed on the screen, the background image of the person to be analyzed, and the like.

The clustering unit 15 clusters the change in the biological reaction determined to be specific by the peculiarity determination unit 13 (for example, one or a combination of eye gaze, pulse, facial movement, statement content, and voice quality), and the peculiarity Analyzing the degree of correlation with an event (event identified by the related event identification unit 14) that occurs when a change in biological reaction occurs, and if it is determined that the correlation is at a certain level or more , to cluster the subjects or events based on the correlation analysis results.

For example, if a change in a specific biological reaction corresponds to a negative emotional change, and the event occurring when the specific change in biological reaction occurs is also a negative event, a certain level The above correlation is detected. The clustering unit 15 clusters the person to be analyzed or the event into one of a plurality of pre-segmented categories according to the content of the event, the degree of negativity, the magnitude of the correlation, and the like.

Similarly, if a specific change in biological reaction corresponds to a positive emotional change and the event occurring when the specific change in biological reaction occurs is also a positive event, Level or higher correlations are detected. The clustering unit 15 clusters the person to be analyzed or the event into one of a plurality of pre-segmented classifications according to the content of the event, the degree of positivity, the degree of correlation, and the like.

The analysis result notification unit 16 reports at least one of the changes in the biological reaction determined to be specific by the peculiar determination unit 13, the event identified by the related event identification unit 14, and the classification clustered by the clustering unit 15. , to notify the designator of the subject of analysis (the subject of analysis or the organizer of the online session).

For example, the analysis result notification unit 16 recognizes that when a change in a specific biological reaction that is different from that of the other person occurs in the person to be analyzed (one of the three patterns described above; the same applies hereinafter), the analysis target is Notifies the person to be analyzed of his/her own behavior. This allows the person to be analyzed to understand that he/she has a different feeling from others when he or she performs a certain behavior. At this time, the person to be analyzed may also be notified of the change in the specific biological reaction identified for the person to be analyzed. Furthermore, the person to be analyzed may be further notified of the change in the biological reaction of the other person to be compared.

For example, the words and deeds of the person to be analyzed performed without being particularly conscious of their usual emotions, or the words and deeds of the person to be analyzed consciously accompanied by certain emotions, and the emotions and behaviors that others received When the emotion held by the person to be analyzed is different from the feeling held by the person to be analyzed at the time, the person to be analyzed is notified of the speech and behavior of the person to be analyzed at that time. As a result, it is possible to discover behaviors that are well received by others or behaviors that are not well received by others, contrary to one's own consciousness.

In addition, the analysis result notification unit 16 notifies the organizer of the online session of the event occurring when the person to be analyzed undergoes a specific change in biological reaction that is different from that of the other person, together with the change in the specific biological reaction. to notify. As a result, the organizer of the online session can know what kind of event affects what kind of emotional change as a phenomenon specific to the specified analysis subject. Then, it becomes possible to perform appropriate treatment on the person to be analyzed according to the grasped contents.

In addition, the analysis result notification unit 16 notifies the organizer of the online session of the event occurring when a specific change in biological reaction occurs in the analysis subject, which is different from that of others, or the clustering result of the analysis subject. do. As a result, online session organizers can grasp behavioral tendencies peculiar to analysis subjects and predict possible future behaviors and situations, depending on which classification the specified analysis subjects have been clustered into. be able to. Then, it becomes possible to take appropriate measures for the person to be analyzed.

In the above embodiment, the biological reaction index value is calculated by quantifying the change in biological reaction according to a predetermined standard, and the analysis subject is analyzed based on the biological reaction index value calculated for each of the plurality of people. Although the example of determining whether the change in the biological reaction received is specific compared to others has been described, the present invention is not limited to this example. For example, it may be as follows.

That is, the biological reaction analysis unit 12 analyzes the movement of the line of sight for each of a plurality of people and generates a heat map indicating the direction of the line of sight. The peculiar determination unit 13 compares the heat map generated for the person to be analyzed by the biological reaction analysis unit 12 with the heat map generated for the other person, so that the change in the biological reaction analyzed for the person to be analyzed It is determined whether it is specific compared with the change in biological response analyzed for.

Thus, in the present embodiment, moving images of a video session are stored in the local storage of the user terminal 10, and the above analysis is performed on the user terminal 10. Although it may depend on the machine specs of the user terminal 10, it is possible to analyze the moving image information without providing it to the outside.

<Functional configuration example 2>
As shown in FIG. 4, the video session evaluation system of this embodiment may include a moving image acquisition unit 11, a biological reaction analysis unit 12, and a reaction information presentation unit 13a as functional configurations.

The reaction information presentation unit 13a presents information indicating changes in biological reactions analyzed by the biological reaction analysis unit 12, including participants not displayed on the screen. For example, the reaction information presenting unit 13a presents information indicating changes in biological reactions to an online session leader, moderator, or administrator (hereinafter collectively referred to as the organizer). Hosts of online sessions are, for example, instructors of online classes, chairpersons and facilitators of online meetings, coaches of sessions for coaching purposes, and the like. An online session host is typically one of the users participating in the online session, but may be another person who does not participate in the online session.

By doing so, the organizer of the online session can also grasp the state of the participants who are not displayed on the screen in an environment where the online session is held by multiple people.

<Functional configuration example 3>
FIG. 5 is a block diagram showing a configuration example according to this embodiment. As shown in FIG. 5, in the video session evaluation system of the present embodiment, functions similar to those of the above-described first embodiment are given the same reference numerals, and description thereof may be omitted.

The system according to this embodiment includes a camera unit that acquires images of a video session, a microphone unit that acquires audio, an analysis unit that analyzes and evaluates moving images, and information obtained by evaluating the acquired moving images. an object generator for generating a display object (described below) based on the display; and a display for displaying both the moving image of the video session and the display object during execution of the video session.

The analysis unit includes the moving image acquisition unit 11, the biological reaction analysis unit 12, the peculiar determination unit 13, the related event identification unit 14, the clustering unit 15, and the analysis result notification unit 16, as described above. The function of each element is as described above.

As shown in FIG. 6, the object generation unit generates an object 50 representing the recognized face part and the above-mentioned Information 100 indicating the content of the analysis/evaluation performed is superimposed on the moving image and displayed. The object 50 may identify and display all faces of a plurality of persons when the faces of the plurality of persons are moved in the moving image.

In addition, the object 50 is, for example, when the camera function of the video session is stopped at the other party's terminal (that is, it is stopped by software within the application of the video session instead of physically covering the camera). If the other party's face is recognized by the other party's camera, the object 50 or the object 100 may be displayed in the part where the other party's face is located. This makes it possible for both parties to confirm that the other party is in front of the terminal even if the camera function is turned off. In this case, for example, in a video session application, the information obtained from the camera may be hidden while only the object 50 or object 100 corresponding to the face recognized by the analysis unit is displayed. Also, the video information acquired from the video session and the information recognized by the analysis unit may be divided into different display layers, and the layer relating to the former information may be hidden.

The object 100 in this embodiment may be, for example, an icon corresponding to an emotion (smile icon, sadness icon, anger icon, surprise icon, etc.). Displaying such icons makes it easier to intuitively understand the other party's emotions. Also, as shown in FIG. 7, depending on the degree (intensity) of emotion expression, the number of corresponding icons may be increased, or the size of the corresponding icon may be increased (not shown). good too.

When there are multiple moving image display areas, the

objects

50 and 100 may be displayed in all areas or only in some areas. For example, as shown in FIG. 7, it may be displayed only on the moving image on the guest side.

The embodiments of the invention described in functional configuration example 1 to functional configuration example 3 described above may be implemented as a single device, or a plurality of devices (for example, cloud servers) partially or wholly connected by a network. and the like. For example, the control unit 110 and the storage 130 of each terminal 10 may be realized by different servers connected to each other via a network. That is, the system includes

user terminals

10, 20, a video session service terminal 30 for providing an interactive video session to the

user terminals

10, 20, and an evaluation terminal 40 for evaluating the video session, Variation combinations of the following configurations are conceivable.
(1) Processing everything only on the user terminal As shown in FIG. 8, by performing the processing by the analysis unit on the terminal that is performing the video session (although a certain processing capacity is required), the video session can be performed. Analysis/evaluation results can be obtained at the same time (in real time) as you are.
(2) Processing by User Terminal and Evaluation Terminal As shown in FIG. 9, an analysis unit may be provided in an evaluation terminal connected via a network or the like. In this case, the moving images acquired by the user terminal are shared with the evaluation terminal at the same time as or after the video session, and are analyzed and evaluated by the analysis unit in the evaluation terminal. Together with or separately from the moving image data (that is, information including at least analysis data) is shared with the terminal and displayed on the display unit.

The following system is realized using each configuration of functional configuration example 1 to functional configuration example 3 or a combination thereof.

<Embodiment>
The moving image analysis system according to the present embodiment analyzes a moving image obtained by shooting a user in an environment where an online session is held by a plurality of users regardless of whether or not the user is displayed on the screen during the online session. It is a moving image analysis system that analyzes user reactions.

As shown in FIG. 10, the present system includes, in addition to the analysis units of functional configuration examples 1 to 3 described above, a moving image acquiring unit that acquires moving images of a video meeting, and an analyzing unit that analyzes the acquired moving images. and a statistical information generating unit that statistically performs predetermined evaluations on users and participants to generate statistical information.

The statistical information generation unit analyzes the changes in biological reactions described above for users and participants, and generates statistical information regarding compatibility between users and participants. Statistical information on compatibility can be obtained from various viewpoints, such as the appearance frequency of smiles, the appearance frequency of fear, the content of conversation, and changes in facial expressions.

The participant analysis unit according to the present embodiment recognizes faces included in the acquired moving image, and information stored in advance as model training data for each recognized face (a face feature value and a name are associated with each other). data set) to identify the names of the participants. Note that, for example, proper nouns included in the video meeting schedule, title, etc. may be used in a supplementary combination. Furthermore, by analyzing the user's voice, it is also possible to supplementally combine and use calls to participants ("Mr. Suzuki", "Mr. Ichiro", etc.).

In addition, the statistical information generation unit may include the meeting time of the user and the participants in the video meeting, each speech time, speech frequency, order of speech, and spoken words.

The statistical information generation unit may generate information regarding changes in current and past statistical information of users and participants. For example, including how the current statistical information has changed compared to the statistical information generated in the past (such as a change in the expression of a predetermined emotion, such as whether the smile has increased or decreased) good too.

As described above, according to the present embodiment, the participants can be automatically recognized from the moving image of the video meeting, and the user can obtain statistical information about the participants with whom the video meeting took place. Become.

The processes described using the flowcharts in this specification do not necessarily have to be executed in the illustrated order. Some processing steps may be performed in parallel. Also, additional processing steps may be employed, and some processing steps may be omitted.

The embodiments described above may be combined as appropriate and implemented. Also, the effects described herein are merely illustrative or exemplary, and are not limiting. In other words, the technology according to the present disclosure can produce other effects that are obvious to those skilled in the art from the description of this specification, in addition to or instead of the above effects.

10, 20 user terminal 22 location information acquisition unit 23 event information acquisition unit 24 statistical information generation unit 25 output unit 30 video session service terminal 40 evaluation terminal

Claims

In an environment where a video meeting is held with a plurality of users, the reaction of the user is analyzed based on the moving image obtained by shooting the user regardless of whether or not the user is displayed on the screen during the video meeting. A moving image analysis system for
a moving image acquisition unit that acquires a moving image obtained by shooting the user during the video meeting;
a participant analysis unit that analyzes the acquired moving image to identify participants;
a statistical information generating unit that generates statistical information including at least information of the participants who have had the video meeting with the user;
Video meeting evaluation terminal.
A video meeting evaluation terminal according to claim 1, comprising:
an analysis unit that analyzes changes in biological reactions of the user based on the moving image acquired by the moving image acquisition unit;
A providing unit that provides the result of the analysis to the user,
Video meeting evaluation terminal.
A video meeting evaluation terminal according to claim 2, comprising:
The statistical information generation unit generates statistical information about compatibility between the user and the participant based on the results of analyzing changes in the biological reactions of both the user and the participant.
Video meeting evaluation terminal.
A video meeting evaluation terminal according to claim 2 or claim 3,
The participant analysis unit identifies a name by recognizing the face included in the acquired moving image and referring to information stored in advance based on each face.
Video meeting evaluation terminal.
The video meeting evaluation terminal according to any one of claims 2 to 4,
The statistical information generation unit includes at least one of meeting time of users and participants in the video meeting, speech time of each, speech frequency, order of speech, and words spoken,
Video meeting evaluation terminal.
The video meeting evaluation terminal according to any one of claims 2 to 5,
The statistical information generator generates information about changes in current and past statistical information of the user and the participant.
Video meeting evaluation terminal.
A video meeting evaluation terminal according to claim 1, comprising:
further comprising an emotion evaluation unit that evaluates the degree of emotion of the user according to an evaluation criterion leveled among a plurality of users based on changes in the biological reaction;
The emotion evaluation unit determines the degree of emotion based on the magnitude of the difference between the current biological reaction and the normal biological reaction, and the degree of emotion adjusted according to the likelihood of the same emotion occurring by the user. evaluate,
Video meeting evaluation terminal.
A video meeting evaluation terminal according to claim 1, comprising:
whether or not the change in the biological reaction analyzed for the user with respect to one video meeting is specific compared to the change in the biological reaction analyzed for the user with respect to the video meeting temporally earlier than the one video meeting; determining and clustering the patterns of changes in biological responses based on the content of the changes in biological responses determined to be specific and the magnitude of the change from before;
Video meeting evaluation terminal.
A video meeting evaluation terminal according to claim 1, comprising:
Analyzing the movement of the eyes of each of the plurality of users to generate a heat map indicating the direction of the eyes, and analyzing the user by comparing the generated heat map with the heat maps generated for other users A determination unit that determines whether the change in the biological reaction obtained is specific compared to the change in the biological reaction analyzed for the other user,
Video meeting evaluation terminal.
A video meeting evaluation terminal according to claim 1, comprising:
Determining whether the change in the biological reaction analyzed for the user is specific compared to the change in the biological reaction analyzed for another user, and the biological reaction determined to be specific to the user identifying an event occurring with respect to at least one of the user, the other user, or the environment when a change occurs in the user, and analyzing the degree of correlation between the change in the user's biological reaction and the event , clustering the user or the event based on the analysis result of the correlation when it is determined that the correlation is equal to or higher than a certain level;
Video meeting evaluation terminal.