JP2014050649A - Feebleness evaluation device, feebleness evaluation method, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a feebleness evaluation device for evaluating the feebleness of a user viewing a projected image.SOLUTION: A feebleness evaluation device for performing the feebleness evaluation of a user for viewing a projected image, comprises: reference value storage means for storing the value, which is obtained on the basis of organic data acquired from the user having viewed a predetermined image before the user views an object image to be subjected to the feebleness evaluation of the user, as a reference value for the feebleness evaluation; and feebleness evaluation means for comparing the measured value, which is obtained on the basis of organism data acquired from the user viewing the object image, and the reference value stored in the reference value storing means, thereby to evaluate the feebleness of the user viewing the object image and to output the evaluation result.

Description

  The present invention relates to a technique for evaluating fatigue when providing a video service.

An environment in which stereoscopic video can be viewed on a TV, a game terminal, a mobile terminal, or the like is being prepared, and it can be easily viewed in a home environment (Non-Patent Document 1). However, stereoscopic video services can be viewed using a naked eye monitor, a dedicated glasses-type monitor, or a head-mounted display (HMD). It has been reported and regarded as a problem (Non-Patent Document 2). Therefore, the government and the industry recommend viewing in an appropriate viewing situation (Non-patent Document 3).
On the other hand, efforts are being made to manage daily user health over time using biological measurement techniques (Non-Patent Document 4). By using the biological measurement technique, it is possible to evaluate in real time the feeling of fatigue felt by the user viewing the 3D video.

3D display 3rd honesty, NIKKEI ELECTRONICS 2008.9.22 Poor physical condition due to 3D movie (http://www.kokusen.go.jp/pdf/n-20100804_2.pdf) 3D Consortium Guidelines (http://www.3dc.gr.jp/jp/scmt_wg_rep/guide_index.html) LifeMinder: Wearable health management system (http://ci.nii.ac.jp/naid/110003272519) Construction and experimental evaluation of eye fatigue measurement system using Eye-Sensing Display (http://hydro.energy.kyoto-u.ac.jp/Lab/ronbun/P_2004/nishimura.pdf) Tetsuo Mitsuhashi, "A Study on Measurement and Analysis of CFF and Fatigue of Television Viewers," IEICE (A), vol. J77-A, no. 12, pp.1768-1776, Dec. 1994. Nao Fujimon, "Eye fatigue from the viewpoint of visual information processing mechanism: focusing on the effects of viewing 3D images," New Ophthalmology, vol.14 no. 9, pp.1295-1299, Sept. 1997. Nikon Analytical Image Quality Evaluation Tool VQ-1200, http://www.nikon-sys.co.jp/products/index_1_0.htm NTT Electronics Video Quality Objective Evaluation Software QE1000, http://www.ntt-electronics.com/digital_video/products/qe1000/index.html Sony 3D Quality Control Software MPES-3DQC1 http://www.sony.jp/pro/products/MPES-3DQC1/feature_1.html#L2_10 Correlation between subjective evaluation value and objective measurement value of fatigue due to VDT work http://ci.nii.ac.jp/els/110003676032.pdf?id=ART0004547832&type=pdf&lang=jp&host=cinii&order_no=&ppv_type=0&lang_sw=&no= 1333951089 & cp =

  It is important for a video distribution company to provide a video distribution service comfortably without causing the user to feel tired in order to provide a service with high user satisfaction. For this reason, it is desired to perform quality inspections of video content, a video presentation monitor, and the like in advance to evaluate the user's feeling of fatigue during video viewing. However, in order to evaluate fatigue feeling with high accuracy, there are the following problems.

First, in order to evaluate the user's fatigue feeling objectively in real time, when assessing the fatigue feeling using a biological measurement technique, stable and highly accurate biological measurement is difficult and noise tends to be added to the biological data. It is a problem. Another problem is that biometric data is easily affected by the physical condition of the user on the video viewing date and the environment. In addition, there is a problem that it is difficult to determine whether the cause of fatigue felt by the user is in video viewing or not.
The present invention has been made in view of the above points, and an object of the present invention is to provide a fatigue evaluation technique that enables a user who views a video to evaluate the fatigue of the user with high accuracy.

In order to solve the above-described problem, the present invention is a fatigue evaluation device that performs fatigue evaluation of a user who views a video,
Before the user views the target video for fatigue evaluation, a value obtained based on the biometric data acquired from the user who viewed the predetermined video is stored as a reference value for fatigue evaluation. Reference value storage means;
Fatigue of the user viewing the target video by comparing the measured value obtained based on the biometric data acquired from the user viewing the target video with the reference value stored in the reference value storage means It is configured as a fatigue evaluation device including fatigue evaluation means for evaluating feeling and outputting an evaluation result.
The present invention can also be configured as a fatigue evaluation method executed by the fatigue evaluation apparatus and a program for causing a computer to function as the fatigue evaluation apparatus.

  ADVANTAGE OF THE INVENTION According to this invention, it becomes possible to provide the fatigue feeling evaluation technique which makes it possible to evaluate the fatigue feeling of the user who views an image | video with high precision.

It is a figure which shows the structure of the fatigue feeling evaluation apparatus which concerns on embodiment of this invention. 2 is a diagram illustrating a configuration of an input video control unit 1. FIG. 3 is a diagram illustrating a configuration of a calculation unit 2. FIG. 5 is a flowchart illustrating an operation example of an evaluation unit 400. It is a figure which shows an example of the noise removal of the pupil diameter data in the biometric data processing part. It is a figure which shows an example of the analysis precision improvement of the blink in the biometric data process part. It is a figure which shows the example of an analysis result in the biometric data process part. 6 is a diagram illustrating an example of an analysis result in the video signal processing unit 300. FIG. It is a figure which shows the operation example in the reference value derivation process of the evaluation part. It is a figure which shows the operation example 1 in the fatigue feeling evaluation process of the evaluation part. It is a figure which shows the operation example 2 in the fatigue evaluation process of the evaluation part. It is a figure which shows the operation example 3 in the fatigue feeling evaluation process of the evaluation part.

  Embodiments of the present invention will be described below with reference to the drawings. The embodiment described below is only an example, and the embodiment to which the present invention is applied is not limited to the following embodiment.

(Outline of device configuration and operation)
FIG. 1 is a configuration diagram of a fatigue evaluation apparatus according to an embodiment of the present invention. As shown in FIG. 1, the fatigue evaluation apparatus according to the present embodiment includes an input video control unit 1 and a calculation unit 2. Although not shown in FIG. 1, the fatigue evaluation apparatus is connected with a playback apparatus that plays back video and a biosensor for acquiring user biometric data.

  FIG. 2 shows a configuration diagram of the input video control unit 1. As shown in FIG. 2, the input video control unit 1 includes a test video storage unit 20 and a switch 10. In FIG. 3, the block diagram of the calculation part 2 is shown. As illustrated in FIG. 3, the calculation unit 2 includes a biological data acquisition unit 100, a biological data processing unit 200, a video signal processing unit 300, an evaluation unit 400, and a reference value storage unit 500.

  Hereinafter, an outline of the operation of the fatigue evaluation apparatus having the above configuration will be described.

  The user inputs a request to the fatigue evaluation apparatus using a remote controller or the like. This request is one of a request for deriving a reference value and a request for performing fatigue evaluation. When a request from the user is input to the fatigue evaluation device, the input video control unit 1 (FIG. 2) selects either a test video or an external input video according to the request, and sends it to the calculation unit 2 and the playback device. Output video signal.

  As shown in FIG. 3, the calculation unit 2 receives a request from a user, an input of a video signal from the input video control unit 1, and an input from an external biosensor. The video signal input to the calculation unit 2 is analyzed by the video signal processing unit 300, and the analysis result is input to the evaluation unit 400.

  The biometric data acquisition unit 100 receives a signal from a biometric sensor as input and measures biometric data. The measurement result in the biometric data acquisition unit 100 is analyzed in the biometric data processing unit 200, and the analysis result is input to the evaluation unit 400.

  The evaluation unit 400 performs a reference value derivation process or a fatigue feeling evaluation process in response to a request from the user. In the fatigue evaluation process, the user is viewing a video based on the analysis result of the biological data processing unit 200, the analysis result of the video signal processing unit 300, and the reference value of the reference value storage unit 500 derived by the reference value deriving process. The user's fatigue evaluation is executed, and the evaluation result is returned to the requester. As a result, fatigue evaluation of the user who is viewing the video can be realized.

  As an example, the calculation unit 2 in the fatigue evaluation apparatus according to the present embodiment can be realized by causing a computer to execute a program describing the processing contents described in the present embodiment. In other words, the functions of each unit of the calculation unit 2 execute programs corresponding to the processes performed by the respective units using hardware resources such as a CPU, memory, and hard disk built in the computer constituting the calculation unit 2. This can be realized by doing so. The above-mentioned program can be recorded on a computer-readable recording medium (portable memory or the like), stored, or distributed. It is also possible to provide the program through a network such as the Internet or electronic mail.

  In addition, by providing the input video control unit 1 in the computer, the fatigue evaluation apparatus according to the present embodiment may be realized by the computer, or the computer serving as the calculation unit 2 and the input video control unit 1 A fatigue evaluation device may be realized by combining the following devices (computer or the like). Further, it is possible to employ a configuration in which the calculation unit 2 itself is a fatigue evaluation device, the reference value is obtained by another device, and the reference value is stored in the reference value storage unit 500 in the calculation unit 2 in advance.

(Operation details)
Hereinafter, the operation of each part in the fatigue evaluation apparatus according to the present embodiment will be described in detail.

<Input video control unit 1>
In the input video control unit 1 shown in FIG. 2, the video signal is switched by the switch 10 in response to the input request. When the input request is a reference value derivation request, the switch 10 is connected to the test video storage unit 20 and outputs a test video signal to the playback device and the calculation unit 2. In this case, a test video is output from the playback device, and the user views the test video. On the other hand, if the input request is a request for performing fatigue feeling evaluation, the switch 10 is connected to a playback apparatus that plays back an image that is subject to fatigue evaluation, and the video signal of the playback apparatus is transmitted to the calculation unit 2. Is output. In this case, the user views a video that is subject to fatigue evaluation.

  A test video is stored in the test video storage unit 20. The test video is, for example, “video in which the entire screen is switched between white video and video in which the entire screen is black”, “video including a fast-moving scene”, or the like.

<Calculation unit 2: Evaluation unit 400>
The operation flow of the evaluation unit 400 is shown in FIG. As shown in FIG. 4, the evaluation unit 400 performs a reference value deriving process and a fatigue feeling evaluation process in accordance with the input request. That is, when the input request is a reference value derivation request (Yes in step 1), a reference value derivation process is executed (step 2). In the reference value derivation process in step 2, a reference value such as the user's blink or pupil reaction is derived, and the derivation result is stored in the reference value storage unit 500.

  When the input request is a request for fatigue evaluation (No in Step 1) and when a request for deriving a reference value has already been performed (when data is stored in the reference value storage unit 500) For (Yes in Step 3), fatigue evaluation processing is executed (Step 4). In the fatigue feeling evaluation process in step 4, the fatigue feeling of the user who is viewing the video is evaluated based on the analysis result of the biological data processing unit 200, the analysis result of the video signal processing unit 300, and the reference value of the reference value storage unit 500. To do. In the case of a request for fatigue evaluation (No in Step 1) and in the case where a request for derivation of a reference value is not performed (when data is not stored in the reference value storage unit 500) (No in Step 3) The evaluation unit 400 executes the reference value deriving process and the fatigue feeling evaluation process in this order to evaluate the fatigue feeling (step 5).

<Calculation unit 2: Biometric data acquisition unit 100>
The biometric data acquisition unit 100 measures biometric information of a user who is viewing a video using various biometric sensors in order to acquire biometric information that changes due to fatigue. That is, various generation sensors are connected to the biometric data acquisition unit 100, and the biometric data acquisition unit 100 acquires biometric data obtained by the various generation sensors.

  For example, as described in Non-Patent Document 5, it is known that the behavior of blinking and pupil diameter changes when fatigued. Therefore, in order to capture the behavior of blinks and pupil diameter, measurement is performed with an eye movement measurement device or an electrooculogram (waveform of an electrooculogram signal). It is conventional technology to capture the behavior of blinks and pupil diameters with an eye movement measuring device or an electrooculogram. In addition, blinks can be extracted from EEG measurement data, or the user's eyeballs can be captured with a camera to capture blinks and pupil diameter, and blink and pupil diameter data can be acquired as biometric data using these techniques. Is also possible. Furthermore, it is also known that the critical fusion frequency decreases when fatigued (Non-Patent Document 6), the regulatory response changes (Non-Patent Document 7), and the like, and these are measured as biological information that changes due to fatigue. It is good. The biometric information that changes due to fatigue that can be acquired by the biometric data acquisition unit 100 is not limited thereto.

<Calculation unit 2: Biometric data processing unit 200>
The biological data processing unit 200 receives the measurement result of the biological data acquisition unit 100 and performs data processing. It is known that a large amount of noise is present in biometric data. For example, as shown in the upper part of FIG. Noise removal is necessary to obtain highly accurate data. Specifically, the user's line-of-sight position during video viewing does not deviate significantly between the left and right eyes, so when one-eye line of sight position data of the left and right eyes is pointing outward from the monitor. There is a method of removing data at that time.

  In addition, since the left and right eyes watching the video are watching the same brightness and the influence of the external environment such as humidity is the same, the pupil diameters of both eyes are not extremely different. It is possible to remove noise by comparing the size of the pupil diameter of the eye (which is an example of two biological data) and removing the data at that time if there is an extreme difference in size. (Bottom of FIG. 5). In this case, when the biometric data processing unit 200 performs the process, for example, when the difference in the size of the pupil diameter between the left and right eyes is larger than a predetermined threshold value, the process of removing the data at that time is performed.

  Although it is conceivable to detect blinks from the pupil diameter size or electrooculogram, in this embodiment, the accuracy is improved by using both (an example of two biological data). For example, an electrooculogram can be measured with high accuracy because it directly measures the movement of the eye muscles by attaching electrodes directly to the eyelids, but in the case of a long blink (once), the muscles when the eyes are closed and opened Since the activity occurs, there is a demerit that there is a possibility of false detection twice (the upper part of FIG. 6). Therefore, by comparing the electrooculogram data with the size of the pupil diameter, it is possible to improve the detection accuracy of the blink (lower part of FIG. 6). In the example shown in FIG. 6, there are two waveform peaks that can be determined as blinks in the electrocardiogram. In the two waveform peak sections, the pupil diameter data is almost zero. Since this indicates that the eyes are closed, it can be determined that the two waveform peaks in the electrooculogram correspond to when the eyes are closed and opened in one blink. For example, when the biometric data processing unit 200 detects that two peaks have occurred within a predetermined time interval in the electrooculogram, the biological data processing unit 200 refers to the pupil diameter data of the time interval of the two peaks, as shown in FIG. As shown in the lower part, if the pupil diameter is approximately 0, a process of determining that two peaks in the electrocardiogram are one blink.

  On the other hand, the eye movement measurement device has a demerit that it cannot capture blinks that are not completely closed. Also in this case, by comparing and analyzing the electrooculogram data and the pupil diameter data, the blink detection accuracy can be increased. In this way, using the biological data subjected to the noise removal technique, as shown in FIG. 7, the time interval of the blink, the size of the pupil diameter, the speed of contraction of the pupil diameter, and the like are analyzed, and the analysis from which the noise is removed Output as a result (measured value).

<Calculation unit 2: Video signal processing unit 300>
The video signal processing unit 300 analyzes the motion vector amount between video frames of the input video signal, the average luminance change, the presence or absence of video degradation such as vertical pixel shift of the left and right video of 3D video, and the presence or absence of flicker. (Non-Patent Documents 8, 9, and 10). FIG. 8 shows changes in luminance and motion amount as examples of video analysis results.

<Calculation unit 2: Reference value derivation process of evaluation unit 400>
During the reference value derivation process of the evaluation unit 400, reference values such as the user's blink and pupil reaction are derived. Specifically, the analysis result (illustrated in FIG. 7) in the biometric data processing unit 200 and the analysis result (illustrated in FIG. 8) in the video signal processing unit 300 are compared and associated, and the reference value as shown in FIG. Is stored in the reference value storage unit 500. The type (item) of the reference value is determined in advance. In the example illustrated in FIG. 9, as reference values, the blink rate when there is no movement change, the average pupil diameter size, the maximum pupil diameter contraction speed, the relationship between the brightness of the presented video and the pupil diameter, the amount of motion of the presented video and the pupil Although the relationship with the diameter variation is shown, these are examples, and the reference value is not limited to these.

  Note that the reference value derivation process allows users to watch videos that are subject to fatigue evaluation so that the effects of the physical condition of the viewing date when viewing the images subject to fatigue evaluation and the effects of the viewing environment are added to the reference values. Immediately before, it is desirable to execute in the same environment as the environment for viewing the video for fatigue evaluation.

  If the input request is a reference value derivation request, the reference value is derived based on the analysis result of the video signal and the biological data when the test video is presented. If the input request is a request for fatigue assessment execution and the reference value derivation request has not been executed in advance, the analysis results of the video signal and biological data for the first 10 minutes when viewing the external input video are displayed. A reference value is derived on the basis of this. In this case, the first 10 minutes of video when viewing the external input video may be referred to as “test video”.

<Calculation unit 2: Fatigue evaluation process of evaluation unit 400>
During the fatigue evaluation process of the evaluation unit 400, fatigue evaluation of the user who is viewing the video is performed. As fatigue evaluation, for example, whether the user feels fatigue or not is classified into two levels of 0 and 1, or output in multiple stages such as “fatigue level 5”. It is done. In this embodiment, the feeling of fatigue is divided into a plurality of levels. Specifically, the initial level is set to 0, and the fatigue level increases as the level value increases. Specific operations for deriving the fatigue level are shown below.

The feeling of fatigue is evaluated based on the analysis result of the video signal processing unit 300, the analysis result of the biological data processing unit 200, and the reference value of the reference value storage unit 500. Here, a _1t = 1 is set when fatigue is detected based on the blink analysis result, and a _1t = 0 is set when it is not detected (t is the measurement time). If fatigue is detected based on the pupil diameter analysis result, a _2t = 1; otherwise, a _2t = 0. When a feeling of fatigue is detected based on the result of comparison with the reference value in FIG. 9, a _3t = 1 is set, and when not detected, a _3t = 0 is set. Further, based on the analysis result by the video signal processing unit 300, b _t = 1 when it is detected that the presented video is degraded, and b _t = 0 when it is not detected. In the present embodiment, the fatigue level L _t is defined as follows, and the evaluation unit 400 calculates and outputs the fatigue level L _t according to this definition.

なお、上記のようにして疲労感レベルを算出することは一例にすぎない。例えば、基準値記憶部５００の基準値を用いた評価のみで疲労感レベルを算出するようにしてもよい。

Note that calculating the fatigue level as described above is merely an example. For example, the fatigue level may be calculated only by using the reference value stored in the reference value storage unit 500.

Further, when the evaluation unit 400 determines that the presented video is deteriorated from the analysis result of the video signal processing unit 300, it is necessary to correct the presented video. Therefore, when b _t = 1, the evaluation unit 400 performs control to output an alarm. Examples of the “alarm” include, but are not limited to, blinking a lamp attached to the fatigue evaluation device and presenting sound from a speaker attached to the fatigue evaluation device. It should be noted that the means for judging video degradation in the evaluation unit 400 is called deterioration judging means, and the means for controlling alarm output and the means for issuing an alarm (lamp, speaker, etc.) can be collectively called alarm output means.

Hereinafter, a calculation method example of a _1t , a _2t , a _3t , and b _t will be described in more detail. First, the comparison between the blink analysis result and the analysis result of the video signal processing unit 300 will be described with reference to FIGS. As shown in FIG. 10, although the state where the blink interval is less than 1 second continues for 1 minute (detection of fatigue), the result of the video signal processing unit 300 indicates that there is no abnormality in the video. In such a case, there is a possibility that a feeling of fatigue is caused not by the video deterioration but by the long-time video viewing and user viewing environment. Therefore, a _1t = 1 and b _t = 0, and the fatigue level L _t is increased by one step.

  Here, as an example of a criterion for detecting fatigue, “a state where the blink interval is less than 1 second continues for 1 minute” is an example. In the example of the present embodiment, it is assumed that a threshold value, conditions, etc. for fatigue detection are determined by conducting an experiment in advance, and that `` the situation where the blink interval is less than 1 second continued for 1 minute '' It is an example of the detection standard of the fatigue feeling determined in this way.

In addition, when fatigue is detected in this way, as shown in FIG. 11, the result of the video signal processing unit 300 further indicates that the video is degraded, the scene is fast moving, or the video flickers. In the case where it is indicated that the occurrence of the error has occurred, there is a possibility that the user feels tired due to the presented video. Therefore, a _1t = 1 and b _t = 1, and even in this case, the fatigue level L _t is increased and an alarm is output.

In addition, when the user is viewing 3D video, the result of the video signal processing unit 300 is that the left and right eye images are shifted in the horizontal direction and the vertical direction, the luminance is shifted, the size is shifted, etc. When it is shown that there is video degradation, there is a possibility that the blink interval has become shorter (the user feels tired) due to the degradation that has occurred in these presentation videos. Therefore, a _1t = 1 and b _t = 1 are set, the fatigue level Lt is increased by 1, and the alarm is raised.

Further, for example, when the situation where the blink interval exceeds 10 seconds continues, it is assumed that a _1t = 1 and b _t = 0 because the user is watching the video and is easily fatigued. Here, the blink interval is described as 10 seconds, but this is an example. As described above, in the example of the present embodiment, it is determined by performing an experiment in advance, and “blink interval 10 seconds” is an example of the detection criterion determined in this way.

On the other hand, with regard to the pupil diameter, as shown in FIG. 12, when the pupil diameter size change is compared with the luminance change of the presented video, if the pupil diameter size does not change according to the luminance change, the user is fatigued. Since it is considered that a feeling is felt, a _{2 t} = 1 and b _t = 0, and the fatigue feeling level L _t is increased by 1. At this time, if the pupil diameter does not change according to the brightness change because the brightness to be presented is too high, a _2t = 1, b _t = 1, and the fatigue level L _t is increased by 1 and an alarm is output To do. If the change speed of the pupil diameter size is slower than the brightness change speed of the video, it is possible that the user feels tired. Therefore, a _2t = 1 and b _t = 0, and the fatigue level L _t is increased by 1. In addition, if the pupil size is fluctuating regardless of the change in the presentation video, the user may not be able to watch the video correctly or the user's viewing environment may cause fatigue. Therefore, a _2t = 1 and b _t = 0, and the fatigue level L _t is increased.

Next, evaluation using a reference value will be described. Biometric data fluctuates greatly under the influence of the physical condition of the measurement date and the viewing environment. For example, when viewing on a dry day with low humidity, there are more blinks than when viewing on a humid day. Therefore, in this embodiment, the reference value (FIG. 9, right figure) stored in the reference value storage unit 500, which is a value that takes into account the influence of the physical condition of the viewing date and the influence of the viewing environment, and the fatigue evaluation By comparing the analysis result (measurement value) of the biological data at the time, an evaluation value that excludes the influence of the physical condition of the viewing date and the influence of the viewing environment is obtained. For example, the blink rate stored in the reference value storage unit 500 is compared with the blink rate at the time of fatigue evaluation, and when the latter is increased or decreased by 20% or more with respect to the former, It is conceivable that the user's physical condition is worse than before viewing. Therefore, a _3t = 1 and b _t = 0 are set, and the fatigue feeling level L _t is increased. Regarding the relationship between the luminance change of the presented video and the pupil diameter fluctuation, etc., the pupil diameter size corresponding to the brightness of the presented video is read from FIG. 9 and compared with the measured pupil diameter size, it is increased or decreased by 20% or more. If so, it is possible that the user's physical condition is worse than before viewing. Therefore, a _3t = 1 and b _t = 0 are set, and the fatigue feeling level L _t is increased. Here, as an example of fatigue detection criteria, the fatigue detection threshold, conditions, etc. are set to `` 20% or more '' as an example, but as described above, in the example of this embodiment, an experiment was performed in advance. “20% or more” is an example of the fatigue detection criterion determined in this way.

  In addition, after receiving the request, the fatigue feeling evaluation is not performed continuously, but based on the analysis result of the video signal processing unit 300, the fatigue feeling evaluation is not performed in a steady scene, and the luminance change is large. The fatigue evaluation may be performed only in a characteristic scene such as a scene.

(Summary of the embodiment, effects)
As described above, in the present embodiment, biometric information of a user who is viewing a video is measured by a camera or various sensors, and analysis such as noise removal of biometric data is performed. Then, a test video is played before viewing the video, biometric data before viewing the video is acquired, and this value is evaluated as a reference to exclude the influence of the physical condition of the video viewing date and the influence of the viewing environment. Further, in order to evaluate the fatigue caused by the viewing video, the video signal being viewed is analyzed, and an alarm is output if video degradation is detected. By comparing the presence / absence of the alarm with the fatigue evaluation result, it can be determined whether or not the video being viewed is causing the fatigue.

  By using the technique according to the present embodiment, it is possible to efficiently perform a quality check in advance of a video. In addition, if this technology is incorporated into a video distribution system, it is possible to acquire in real time the evaluation results of the feeling of fatigue felt by the user viewing the video. If this evaluation result is used, if the user feels tired due to the viewing video, the user immediately stops viewing. The viewing video is not the cause, but the long viewing time or the user viewing environment When the user feels tired, it is possible to take real-time measures such as prompting the user to take a break. As a result, safer and more secure 3D video services can be provided, and the spread of 3D video services can be expected.

The technology according to the present invention is not limited to the video distribution service, but can be used when it is desired to evaluate the user's fatigue during VDT work. In recent years, the number of VDT workers has increased, and eye strain due to VDT work has increased (Non-Patent Document 11). Therefore, it is conceivable that the user's fatigue is evaluated from the user's biological information and display monitor contents during the VDT work, and a break is encouraged.
The present invention is not limited to the above-described embodiments, and various modifications and applications are possible within the scope of the claims.

DESCRIPTION OF SYMBOLS 1 ... Input video control part 2 ... Calculation part 10 ... Switch 20 ... Test video storage part 100 ... Biometric data acquisition part 200 ... Biometric data processing part 300 ... Video signal processing part 400 ... Evaluation part 500 ... Reference value storage part
t… Measurement time
a _1t ... Result of detecting fatigue from blink fluctuation
a _2t ... Result of detecting fatigue from pupil diameter variation
a _3t ... Result of detection of fatigue by comparison with the reference value
b _t ... The result of detecting an abnormality from the analysis result of the video signal processor
L _t … fatigue level

Claims (7)

A fatigue evaluation device for evaluating fatigue feeling of a user who views a video,
Before the user views the target video for fatigue evaluation, a value obtained based on the biometric data acquired from the user who viewed the predetermined video is stored as a reference value for fatigue evaluation. Reference value storage means;
Fatigue of the user viewing the target video by comparing the measured value obtained based on the biometric data acquired from the user viewing the target video with the reference value stored in the reference value storage means A fatigue evaluation apparatus comprising: a fatigue evaluation means for evaluating feeling and outputting an evaluation result. The fatigue evaluation means
Biometric data acquisition means for acquiring biometric data from the user;
Biometric data processing means for calculating a measurement value from which noise has been removed as the measurement value by comparing the biometric data;
Evaluation means for evaluating the user's fatigue based on the measurement value from which the noise has been removed;
The fatigue evaluation apparatus according to claim 1, further comprising: Video signal processing means for analyzing the video signal of the target video that the user is viewing;
Deterioration determining means for determining whether or not the target video is deteriorated based on the analyzed video signal;
The fatigue evaluation apparatus according to claim 1, further comprising: an alarm output unit that outputs an alarm when the deterioration determination unit determines that the target video is deteriorated. A fatigue feeling evaluation method executed by a fatigue evaluation apparatus that evaluates fatigue feeling of a user who views a video,
Before the user views the target video subject to fatigue evaluation, biometric data is acquired from the user viewing the predetermined video, and the value obtained based on the biometric data is used for fatigue evaluation. A reference value acquisition step for storing the reference value in the reference value storage means;
Fatigue of the user viewing the target video by comparing the measured value obtained based on the biometric data acquired from the user viewing the target video with the reference value stored in the reference value storage means A fatigue feeling evaluation method comprising: a fatigue feeling evaluation step for evaluating feeling and outputting an evaluation result. The fatigue evaluation step includes
A biometric data acquisition step of acquiring biometric data from the user;
A biometric data processing step of calculating a measurement value from which noise has been removed as the measurement value by comparing the biometric data;
An evaluation step for evaluating the user's fatigue based on the measurement value from which the noise has been removed;
The fatigue evaluation method according to claim 4, further comprising: A video signal processing step of analyzing a video signal of the target video that the user is viewing;
A deterioration determination step for determining whether or not the target video is deteriorated based on the analyzed video signal;
The fatigue evaluation method according to claim 4, further comprising: an alarm output step of outputting an alarm when it is determined in the deterioration determination step that the target video is deteriorated.   The program for functioning a computer as each means in the fatigue evaluation apparatus of any one of Claims 1 thru | or 3.

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