JP6142822B2 - Diagnosis support apparatus and diagnosis support method - Google Patents

Description

  The present invention relates to a diagnosis support apparatus and a diagnosis support method.

  Recently, people with developmental disabilities are said to be on the rise. It is known that developmental disabilities are found early and start treatment to reduce symptoms and increase the effect of adapting to society. In Japan, we are aiming for early detection through interviews at the age of 1 and a half. However, there are problems such as shortage of psychiatrists and time-consuming interviews, and the effect is not sufficient. Therefore, there is a need for an objective and efficient diagnosis support device for developmental disabilities.

  For early detection of developmental disabilities, it is ideal to be able to diagnose at the age of 1 and a half years. As developmental disorders, attention deficit / hyperactivity disorder (ADHD (Attention Deficit / Hyperactivity Disorder)) and autism spectrum disorder (ASD (Autistic Spectrum Disorder)) are known. As a characteristic of children with disabilities with ADHD, it is difficult to concentrate on one thing, and the gaze target is not limited, and the gaze point is easy to move. In addition, a characteristic of ASD children with disabilities is that they do not look at their opponent's eyes (turn their eyes away). It is also known that children with disabilities with ASD prefer geometric images rather than human images.

  In addition, a method has been proposed for diagnosing developmental disabilities by applying a method of detecting a gazing point by photographing a human face with a camera and calculating a corneal reflection and a pupil position.

JP 2005-185431 A JP 2008-125619 A JP 2005-198743 A JP 2002-360518 A JP 2011-206542 A

Pierce K et al., “Preference for Geometric Patterns Early in Life as a Risk Factor for Autism.”, Arch Gen Psychiatry. 2011 Jan; 68 (1): 101-109.

  Subjects about one and a half years old tend not to gaze at objects with little movement. For this reason, the conventional method of detecting a gazing point may not be able to support diagnosis appropriately, and a more accurate detection method has been demanded.

  The present invention has been made in view of the above, and an object thereof is to provide a diagnosis support apparatus and a diagnosis support method capable of improving the accuracy of diagnosis.

  In order to solve the above-described problems and achieve the object, the present invention provides a display unit, an imaging unit that images a subject, and a line of sight that detects the gaze direction of the subject from a captured image captured by the imaging unit. A detection unit, a viewpoint detection unit that detects the viewpoint of the subject in a plurality of divided regions obtained by dividing the display region of the display unit, based on the line-of-sight direction, a person image, a pattern image, and a character image An output control unit that displays at least two of them as a diagnostic image in each of the divided regions that are different from each other among the plurality of divided regions, and the detected by the viewpoint detection unit when the diagnostic image is displayed An evaluation unit that calculates an evaluation value of the subject based on a viewpoint.

  The diagnosis support apparatus and diagnosis support method according to the present invention have an effect of improving the accuracy of diagnosis.

FIG. 1 is a diagram illustrating an example of an arrangement of a display unit, a stereo camera, and a light source used in the first embodiment. FIG. 2 is a diagram illustrating an outline of functions of the diagnosis support apparatus according to the first embodiment. FIG. 3 is a block diagram illustrating an example of detailed functions of the respective units illustrated in FIG. FIG. 4 is a diagram illustrating an example of eye and distance detection when two cameras are used. FIG. 5 is an explanatory diagram illustrating an example of a displayed diagnostic image. FIG. 6 is a flowchart illustrating an example of a diagnosis support process according to the first embodiment. FIG. 7 is a flowchart showing an example of the window moving process of FIG. FIG. 8 is a flowchart illustrating an example of the comprehensive evaluation process of FIG. FIG. 9 is a flowchart showing another example of the comprehensive evaluation process of FIG. FIG. 10 is a flowchart showing an example of the area A1 process of FIG. FIG. 11 is a diagram illustrating an example of the arrangement of the display unit, the stereo camera, the infrared light source, and the subject according to the second embodiment. FIG. 12 is a diagram illustrating an example of the arrangement of the display unit, the stereo camera, the infrared light source, and the subject according to the second embodiment. FIG. 13 is a diagram illustrating an outline of functions of the diagnosis support apparatus. FIG. 14 is a block diagram illustrating an example of detailed functions of each unit illustrated in FIG. 13. FIG. 15 is a diagram illustrating an outline of processing executed by the diagnosis support apparatus according to the second embodiment. FIG. 16 is an explanatory diagram showing the difference between the method using two light sources and the second embodiment using one light source. FIG. 17 is a diagram for explaining calculation processing for calculating the distance between the pupil center position and the corneal curvature center position. FIG. 18 is a flowchart illustrating an example of calculation processing according to the second embodiment. FIG. 19 is a diagram illustrating a method of calculating the position of the corneal curvature center using the distance obtained in advance. FIG. 20 is a flowchart illustrating an example of a line-of-sight detection process according to the second embodiment.

  Hereinafter, embodiments of a diagnosis support apparatus and a diagnosis support method according to the present invention will be described in detail with reference to the drawings. In addition, this invention is not limited by this embodiment.

(First embodiment)
As described above, a diagnosis support apparatus for developmental disabilities requires a more accurate method. In addition, there has been a demand for an efficient device capable of supporting diagnosis for various developmental disabilities. So far, for example, a technique has been proposed that supports diagnosis of ADHD by detecting saccade when viewing a screen on which nothing is displayed. The diagnosis support apparatus according to the first embodiment detects and determines a gazing point for a plurality of grouped windows. As a result, diagnosis support for ADHD can be provided with higher accuracy than before, and diagnosis support for ASD can also be realized.

  FIG. 1 is a diagram illustrating an example of an arrangement of a display unit, a stereo camera, and a light source used in the first embodiment. As shown in FIG. 1, in this embodiment, a set of stereo cameras 102 is arranged below the display screen 101. The stereo camera 102 is an imaging unit that can perform stereo shooting with infrared rays, and includes a right camera 202 and a left camera 204.

  Infrared LED (Light Emitting Diode) light sources 203 and 205 are arranged in the circumferential direction immediately before the lenses of the right camera 202 and the left camera 204, respectively. The infrared LED light sources 203 and 205 include an inner peripheral LED and an outer peripheral LED having different wavelengths for emitting light. The pupils of the subject are detected by the infrared LED light sources 203 and 205. As a pupil detection method, for example, the method described in Patent Document 2 can be applied.

  When detecting the line of sight, the space is expressed by coordinates to identify the position. In this embodiment, the center position of the display screen 101 is the origin, the top and bottom are the Y coordinate (up is +), the side is the X coordinate (right is +), and the depth is the Z coordinate (front is +). .

  FIG. 2 is a diagram illustrating an outline of functions of the diagnosis support apparatus 100. FIG. 2 shows a part of the configuration shown in FIG. 1 and a configuration used for driving the configuration. As shown in FIG. 2, the diagnosis support apparatus 100 includes a right camera 202, a left camera 204, infrared LED light sources 203 and 205, a speaker 105, a drive / IF (interface) unit 208, and a control unit 300. A storage unit 150 and a display unit 210. In FIG. 2, the display screen 101 shows the positional relationship between the right camera 202 and the left camera 204 in an easy-to-understand manner, but the display screen 101 is a screen displayed on the display unit 210. The drive unit and the IF unit may be integrated or separate.

  The speaker 105 functions as an audio output unit that outputs an audio or the like for alerting the subject during calibration.

  The drive / IF unit 208 drives each unit included in the stereo camera 102. The drive / IF unit 208 serves as an interface between each unit included in the stereo camera 102 and the control unit 300.

  The storage unit 150 stores various information such as a control program, a measurement result, and a diagnosis support result. The storage unit 150 stores, for example, an image to be displayed on the display unit 210. The display unit 210 displays various information such as a target image for diagnosis.

  FIG. 3 is a block diagram illustrating an example of detailed functions of the respective units illustrated in FIG. As shown in FIG. 3, a display unit 210 and a drive / IF unit 208 are connected to the control unit 300. The drive / IF unit 208 includes camera IFs 314 and 315, an LED drive control unit 316, and a speaker drive unit 322.

  A right camera 202 and a left camera 204 are connected to the drive / IF unit 208 via camera IFs 314 and 315, respectively. The driving / IF unit 208 drives these cameras to image the subject.

  The infrared LED light source 203 includes a wavelength 1-LED 303 and a wavelength 2-LED 304. The infrared LED light source 205 includes a wavelength 1-LED 305 and a wavelength 2-LED 306.

  Wavelength 1-LEDs 303 and 305 emit infrared light having wavelength 1. Wavelength 2-LEDs 304 and 306 irradiate wavelength 2 infrared rays.

  The wavelength 1 and the wavelength 2 are, for example, a wavelength of less than 900 nm and a wavelength of 900 nm or more, respectively. When the reflected light reflected by the pupil is irradiated with infrared light having a wavelength of less than 900 nm, a bright pupil image is obtained as compared with the case where reflected light reflected by the pupil is irradiated with infrared light having a wavelength of 900 nm or more. It is because it is obtained. In addition, about the wavelength of the infrared rays to irradiate, it is not restricted to the above, The result which imaged the reflected light reflected by the pupil by irradiating the infrared rays of wavelength 1, and the reflection reflected by the pupil after irradiating the infrared rays of wavelength 2 What is necessary is just to be able to make a difference with the result of imaging light.

  The speaker driving unit 322 drives the speaker 105. The diagnosis support apparatus 100 may include an interface (printer IF) for connecting to a printer as a printing unit. In addition, the printer may be provided inside the diagnosis support apparatus 100.

  The control unit 300 controls the entire diagnosis support apparatus 100. The control unit 300 includes a line-of-sight detection unit 351, a viewpoint detection unit 352, an output control unit 353, and an evaluation unit 354.

  The gaze detection unit 351 detects the gaze (gaze direction) of the subject from the captured image captured by the imaging unit (stereo camera 102). The process for detecting the line of sight includes a process for detecting the eye position of the subject. The viewpoint detection unit 352 detects the viewpoint of the subject using the detected gaze direction. For example, the viewpoint detection unit 352 detects a viewpoint (gaze point) that is a point that the subject gazes out of the target image displayed on the display screen 101. As a gaze detection method by the gaze detection unit 351 and a viewpoint detection method by the viewpoint detection unit 352, any conventionally used method can be applied. Below, similarly to patent document 3, it demonstrates as an example the case where a test subject's gaze direction and a gaze point are detected using a stereo camera.

  In this case, the gaze detection unit 351 first detects the gaze direction of the subject from the image captured by the stereo camera 102. The gaze detection unit 351 detects the gaze direction of the subject using, for example, the methods described in Patent Documents 1 and 2. Specifically, the line-of-sight detection unit 351 obtains the difference between the image captured by irradiating the infrared light having the wavelength 1 and the image captured by irradiating the infrared light having the wavelength 2, and the image in which the pupil image is clarified. Generate. The line-of-sight detection unit 351 uses the two images generated as described above from the images captured by the left and right cameras (the right camera 202 and the left camera 204) and uses the stereo vision technique to determine the position of the subject's pupil ( Eye position) is calculated. The line-of-sight detection unit 351 calculates the position of the subject's corneal reflection using images taken by the left and right cameras. Then, the gaze detection unit 351 calculates a gaze vector representing the gaze direction of the subject from the position of the pupil of the subject and the corneal reflection position.

  In addition, the detection method of the eye position and the line of sight of the subject is not limited to this. For example, the eye position and line of sight of the subject may be detected by analyzing an image captured using visible light instead of infrared light.

  The viewpoint detection unit 352 detects, for example, the intersection of the line-of-sight vector represented in the coordinate system as shown in FIG. 1 and the XY plane as the gaze point of the subject. When the gaze direction of both eyes is obtained, the gaze point may be measured by obtaining the intersection of the left and right gazes of the subject.

  FIG. 4 is a diagram illustrating an example of eye and distance detection when two cameras (the right camera 202 and the left camera 204) are used. For the two cameras, a camera calibration theory based on a stereo calibration method is applied in advance to obtain camera parameters. As the stereo calibration method, any conventionally used method such as a method using Tsai's camera calibration theory can be applied. Using the eye position detected from the image captured by the right camera 202, the eye position detected from the image captured by the left camera 204, and the camera parameters, the three-dimensional coordinates of the eye in the world coordinate system are obtained. It is done. Thereby, the distance between the eyes and the stereo camera 102 and the pupil coordinates can be estimated. The pupil coordinate is a coordinate value representing the position of the subject's eye (pupil) on the XY plane. The pupil coordinates can be, for example, coordinate values obtained by projecting the eye position expressed in the world coordinate system onto the XY plane. Usually, the pupil coordinates of the left and right eyes are obtained. A diagnostic image is displayed on the display screen 101. As will be described later, the diagnostic image includes, for example, a natural image (such as a person image and a character image) and a pattern image.

  The pattern image is an image (geometric image) including one or more geometric patterns, for example. The natural image may be a natural object or an image reminiscent of a natural object other than a geometric image. For example, an image (still image or moving image) obtained by capturing a person, an animal, a plant, a natural landscape, or the like with a camera may be used as the natural image. Moreover, you may use the image (still image, moving image) of the character imitating a person, an animal, etc. as a natural image.

  Returning to FIG. 3, the output control unit 353 controls the output of various information to the display unit 210, the speaker 105, and the like. For example, the output control unit 353 controls the output to the display unit 210 such as the diagnostic image and the evaluation result by the evaluation unit 354. The output control unit 353 causes at least two of the person image, the geometric image, and the character image to be displayed as diagnostic images in different divided areas among the plurality of divided areas. The divided area represents an area obtained by dividing the display area (display screen 101) of the display unit 210. A specific example of the divided area will be described later.

  The evaluation unit 354 calculates an evaluation value as an index related to the degree of developmental disability based on the diagnostic image and the gazing point detected by the viewpoint detection unit 352. The evaluation unit 354, for example, based on the position of the gaze point of the subject when a diagnostic image as illustrated in FIG. 5 described later is displayed, the movement distance of the gaze point within the predetermined period, the movement speed of the gaze point within the predetermined period. Then, an evaluation value is calculated based on at least one of the number of detected gazing points in the divided areas within a predetermined period and the number of times the gazing point has moved between a plurality of divided areas within the predetermined period. The evaluation unit 354 may calculate the evaluation value based on the diagnostic image and the gazing point, and the calculation method is not limited to the embodiment.

  FIG. 5 is an explanatory diagram illustrating an example of a displayed diagnostic image. As shown in FIG. 5, the display screen 101 is divided into a plurality of divided areas. Hereinafter, the divided area is also referred to as an area. In the example of FIG. 5, the display screen 101 is divided into four areas A1, A2, A3, and A4. The number of areas is not limited to four.

  In the present embodiment, each area is further divided into four regions (partial regions). Below, the area | region which divided | segmented the area is also called a window. In the example of FIG. 5, each area is further divided into four windows. In addition, it may be configured such that one diagnostic image is displayed in each area without further dividing the area.

  In the area A1, four windows W1, W2, W3, and W4 are set. A person image (person image) is displayed in the windows W1, W2, W3, and W4. Here, each video (image) may be either a still image or a moving image, but a moving image is a preferred form because it is easier to watch. In the area A2, four windows W5, W6, W7, and W8 are set. Animal images (animal images) as character images are displayed in the windows W5, W6, W7, and W8. In the area A3, four windows W9, W10, W11, and W12 are set. A geometric image (geometric image) is displayed in the windows W9, W10, W11, and W12. In the area A4, four windows W13, W14, W15, and W16 are set. A vehicle image (vehicle image) as a character image is displayed in the windows W13, W14, W15, and W16.

  Note that the output control unit 353 may be configured to change an area for displaying a diagnostic image in a plurality of measurement periods (first period, second period). In this case, the evaluation unit 354 may obtain an average value of evaluation values calculated in each period as a final evaluation value. For example, the evaluation values calculated for each of the two patterns in which the positions of the areas A1 and A3 and the areas A2 and A4 are exchanged may be averaged. As a result, it is possible to eliminate the influence of gaze preference (always starting to watch from the upper right).

  Next, diagnosis support processing by the diagnosis support apparatus 100 according to the first embodiment configured as described above will be described with reference to FIGS. FIG. 6 is a flowchart illustrating an example of a diagnosis support process in the present embodiment. It is assumed that the individual calibration has been completed before this. The calibration includes camera calibration as described above and calibration for eye-gaze detection (eye-gaze detection calibration).

  First, the output control unit 353 starts reproduction of a video (diagnostic image) (step S101). The output control unit 353 resets a timer that determines the video playback time (step S102). The evaluation unit 354 clears (initializes) the cumulative value (cumulative distance) of the movement distance of the gazing point during the video reproduction period stored in the storage unit 150 or the like (step S103).

The evaluation unit 354 resets (initializes) the following counters used for calculating the evaluation value (step S104).
Area counters CA1 to CA4 that increment when there is a gazing point in the area
Window counters CW1 to CW16 that increment when there is a gazing point in the window
-Window movement counter CM that increments when the point of interest moves from one window to another

The evaluation unit 354 clears (initializes) the following information used for calculating the evaluation value (step S105).
-Window OK flags FW1 to FW16 for setting 1 when a gazing point exists in each window
-Current window NW indicating a window in which a gazing point is detected at the current or past recent time

  Next, the viewpoint detection unit 352 detects a gazing point (step S106). The viewpoint detection unit 352 determines whether or not gaze point detection has failed due to the influence of blinking or the like (step S107). When blinking occurs, the pupil cannot be detected, so that it is impossible to detect the gazing point. If the gazing point detection fails (step S107: Yes), the process proceeds to step S120. When the gazing point can be detected (step S107: No), the process proceeds to step S108.

  In step S108, the viewpoint detection unit 352 determines whether the coordinates of the gazing point are within the area A1 (step S108). If it is within the area A1 (step S108: Yes), the process proceeds to step S109. In step S109, the viewpoint detection unit 352 performs a process corresponding to the area A1 (area A1 process) (step S109). Details of the area A1 process will be described later. If it is not the area A1 (step S108: No), the process proceeds to step S110.

  In step S110, the viewpoint detection unit 352 determines whether or not the coordinates of the gazing point are within the area A2 (step S110). If it is within the area A2 (step S110: Yes), the process proceeds to step S111. In step S111, the viewpoint detection unit 352 performs a process corresponding to the area A2 (area A2 process) (step S111). When it is not area A2 (step S110: No), it progresses to step S112.

  In step S112, the viewpoint detection unit 352 determines whether or not the coordinates of the gazing point are within the area A3 (step S112). If it is within the area A3 (step S112: Yes), the process proceeds to step S113. In step S113, the viewpoint detection unit 352 performs a process corresponding to the area A3 (area A3 process) (step S113). When it is not area A3 (step S112: No), it progresses to step S114.

  In step S114, the viewpoint detection unit 352 determines whether or not the coordinates of the gazing point are within the area A4 (step S114). If it is within the area A4 (step S114: Yes), the process proceeds to step S115. In step S115, the viewpoint detection unit 352 performs a process corresponding to area A4 (area A4 process) (step S115). If it is not the area A4, for example, if the point of interest is outside the display screen (step S114: No), the process proceeds to step S116.

  In step S116, the viewpoint detection unit 352 calculates the distance between the coordinates of the current gazing point and the coordinates of the previous gazing point (step S116). Next, the viewpoint detection unit 352 adds the distance calculated this time to the accumulated distance (step S117). Next, the viewpoint detection unit 352 substitutes the coordinates of the current gazing point for the coordinates of the previous gazing point (step S118). Next, the viewpoint detection unit 352 executes window movement processing (step S119). Details of the window moving process will be described later.

  Next, the output control unit 353 determines whether or not the video has been reproduced (step S120). For example, the output control unit 353 determines whether or not the reproduction of the video has ended based on whether or not the timer has reached a predetermined value (reproduction time). If the reproduction of the video has not ended (step S120: No), the process returns to step S106 and is repeated. When the video reproduction is finished (step S120: Yes), the process proceeds to step S121.

  The output control unit 353 stops the video reproduction (step S121). The evaluation unit 354 acquires the cumulative distance of gazing point movement (step S122). Further, the evaluation unit 354 calculates an average speed of movement of the gazing point from the accumulated distance and the playback time of the video (step S123). Next, the evaluation unit 354 acquires the values of the area counters CA1 to CA4, acquires the values of the window counters CW1 to CW16, and acquires the value of the window movement counter CM (Step S124). Next, the evaluation unit 354 displays the geometric video for the total number of gazing points detected in the area (area A1) where the person video is displayed and the area (area A3) where the geometric video is displayed. The ratio ANS of the number of gazing points detected in the area (area A3) is obtained (step S125). The ratio ANS indicates the ratio of viewing the geometric image out of the person image and the geometric image. The higher the ratio ANS, the higher the possibility of ASD.

  The evaluation value used for ASD diagnosis support is not limited to the ratio ANS. For example, a value based on the difference between the number of gazing points detected in the area where the person video is displayed and the number of gazing points detected in the area where the geometric video is displayed may be used as the evaluation value. In the present embodiment, the person image and the geometric image are compared. However, the ratio and the number of gazing points between the person image and the character image (animal image or vehicle image) may be compared, and the character image and the geometric image may be compared. You may compare the ratio and number of points of interest with academic video. When comparing the person image and the character image, the higher the rate of gazing at the character image, the higher the possibility of ASD. When comparing the character image and the geometric image, the higher the rate of gazing at the geometric image, The possibility of ASD is high.

  Next, the evaluation unit 354 acquires window OK flags FW1 to FW16 (step S126). The window OK flag changes from 0 to 1 when the corresponding window is watched once. Window OK flags FW1 to FW16 correspond to windows W1 to W16, respectively. The evaluation unit 354 determines which window has been viewed based on the window OK flag.

  Finally, the evaluation unit 354 performs comprehensive evaluation (step S127). Details of the comprehensive evaluation process will be described later.

  FIG. 7 is a flowchart showing an example of the window moving process (step S119) of FIG. First, the viewpoint detection unit 352 determines whether the current window is the same as the previous window (step S201).

  As described above, the current window is a window in which a gazing point is detected at the current or past recent time. If a gazing point is detected at the current time (step S107: No) and a gazing point is detected in any of the windows in each area, the window in which the gazing point is detected at the current time becomes the current window. On the other hand, if a gazing point is detected at the present time (step S107: No), but the gazing point is not included in any of the windows in each area, the current window is not updated. In other words, the window in which the gazing point is detected at a past time that is not the current time becomes the current window.

  The previous window is a window in which a gazing point is detected immediately before the current window. The current window and the previous window are initialized at the start of the diagnosis support process, for example. When a gazing point is detected for the first time in any of the windows, the previous window has been initialized, so the current window may be substituted for the previous window and the window moving process may be terminated.

  When the current window is the same as the previous window (step S201: Yes), the viewpoint detection unit 352 ends the window movement process. If they are not the same (step S201: No), the viewpoint detection unit 352 increments the window movement counter CM (step S202). Next, the viewpoint detection unit 352 substitutes the current window for the previous window (step S203). Thus, each time the point of sight moves between windows, the value of the window movement counter CM is incremented by one.

  The window moving process is a process for confirming the movement of the gazing point between windows. Therefore, if the gazing point is detected at a place other than the window, it is ignored because it is not related to the movement between the windows.

  FIG. 8 is a flowchart showing an example of the comprehensive evaluation process (step S127) of FIG. First, the evaluation unit 354 determines whether the cumulative distance of the gazing point is greater than the threshold value B1 (step S301). If larger (step S301: Yes), the evaluation unit 354 outputs an evaluation result indicating that there is a possibility of ADHD (step S305).

  When the cumulative distance is equal to or less than the threshold B1 (step S301: No), the evaluation unit 354 determines whether the average moving speed of the gazing point is larger than the threshold B2 (step S302). If larger (step S302: Yes), the evaluation unit 354 outputs an evaluation result indicating that there is a possibility of ADHD (step S305).

  When the average moving speed is equal to or less than the threshold B2 (step S302: No), the evaluation unit 354 determines whether the value of the window movement counter CM is larger than the threshold B3 (step S303). If larger (step S303: Yes), the evaluation unit 354 outputs an evaluation result indicating that there is a possibility of ADHD (step S305).

  When the value of the window movement counter CM is equal to or smaller than the threshold B3 (step S303: No), the evaluation unit 354 determines whether the number of window OK flags = 1 is larger than the threshold B4 (step S304). If larger (step S304: Yes), the evaluation unit 354 outputs an evaluation result indicating that there is a possibility of ADHD (step S305).

  When the number of window OK flags = 1 is equal to or less than the threshold value B4 (step S304: No), or after step S305, the evaluation unit 354 determines whether the ratio ANS that is the evaluation value of ASD is greater than the threshold value B5. (Step S306). If larger (step S306: Yes), the evaluation unit 354 outputs an evaluation result indicating that there is a possibility of ASD (step S307). When the ratio ANS is equal to or less than the threshold B5 (step S306: No), or after step S307, the comprehensive evaluation process is terminated.

  In addition, the comprehensive evaluation process of FIG. 8 is an example, and is not limited thereto. As described above, based on the position of the gazing point, the evaluation unit 354 moves the gazing point movement distance (cumulative distance, etc.), the gazing point movement speed (average movement speed, etc.), and the number of gazing points detected in the area. An evaluation value based on at least one of (the total number of window OK flags, etc.) and the number of times the gazing point has moved between areas (window movement counter, etc.) may be calculated.

  In the present embodiment, the diagnostic value can be calculated by displaying different diagnostic images for each area obtained by dividing the display area, so that the accuracy of diagnosis can be improved.

  FIG. 9 is a flowchart showing another example of the comprehensive evaluation process (step S127) of FIG. First, the evaluation unit 354 calculates a ratio P1 of the cumulative distance of the gazing point with respect to the average value AV1 of the cumulative distance (step S401). The evaluation unit 354 calculates a ratio P2 of the average moving speed of the gazing point with respect to the average value AV2 of the average moving speed (step S402). The evaluation unit 354 calculates a ratio P3 of the value of the window movement counter CM with respect to the average value AV3 of the CM values (Step S403). The evaluation unit 354 calculates a ratio P4 of the number of window OK flags = 1 to the average value AV4 of the number of window OK flags = 1 (step S404).

  For the average values AV1, AV2, AV3, and AV4, for example, average values of cumulative distance, average moving speed, window moving counter CM, and number of window OK flags = 1 calculated from a large number of subjects are used. .

  Next, the evaluation unit 354 obtains an ADHD evaluation value E, which is the sum of values obtained by multiplying the ratios P1 to P4 by weighting coefficients (K1 to K4), respectively (step S405). Next, the evaluation unit 354 determines whether the ADHD evaluation value E is greater than the threshold value B6 (step S406). If larger (step S406: Yes), the evaluation unit 354 outputs an evaluation result indicating that there is a possibility of ADHD (step S407).

  When the ADHD evaluation value E is equal to or less than the threshold value B6 (step S406: No), or after step S407, the evaluation unit 354 determines whether the ratio ANS that is the evaluation value of ASD is greater than the threshold value B5 (step S407). S408). If larger (step S408: Yes), the evaluation unit 354 outputs an evaluation result indicating that there is a possibility of ASD (step S409). When the ratio ANS is equal to or less than the threshold value B5 (step S408: No), or after step S409, the comprehensive evaluation process is terminated.

  FIG. 10 is a flowchart showing an example of the area A1 process (step S109) in FIG. The area A1 process is based on the premise that the current gazing point exists in the area A1 based on the determination in step S108.

  First, since the gazing point exists in the area A1, the viewpoint detection unit 352 increments the area counter CA1 (step S501).

  The viewpoint detection unit 352 determines whether or not there is a gazing point in the window W1 in the area A1 (step S502). When the gazing point is not in W1 (step S502: No), the process proceeds to step S506. When the gazing point is in W1 (step S502: Yes), the process proceeds to step S503. In step S503, the viewpoint detection unit 352 increments the window counter CW1 and sets the current window to W1 (step S503).

  Next, the viewpoint detection unit 352 determines whether or not the window OK flag FW1 is 0 (step S504). When FW1 = 0 (step S504: Yes), the viewpoint detection unit 352 sets FW1 = 1 and ends the area A1 process (step S505). If FW1 = 1 already (step S504: No), the area A1 process is terminated.

  In step S506, the viewpoint detection unit 352 determines whether or not there is a gazing point in the window W2 in the area A1 (step S506). When the gazing point is not in W2 (step S506: No), the process proceeds to step S510. If the gazing point is within W2 (step S506: Yes), the process proceeds to step S507. In step S507, the viewpoint detection unit 352 increments the window counter CW2 and sets the current window to W2 (step S507).

  Next, the viewpoint detection unit 352 determines whether or not the window OK flag FW2 is 0 (step S508). When FW2 = 0 (step S508: Yes), the viewpoint detection unit 352 sets FW2 = 1 and ends the area A1 process (step S509). If FW2 = 1 already (step S508: No), the area A1 process is terminated.

  In step S510, the viewpoint detection unit 352 determines whether or not there is a gazing point in the window W3 in the area A1 (step S510). When the gazing point is not in W3 (step S510: No), the process proceeds to step S514. When the gazing point is in W3 (step S510: Yes), the process proceeds to step S511. In step S511, the viewpoint detection unit 352 increments the window counter CW3 and sets the current window to W3 (step S511).

  Next, the viewpoint detection unit 352 determines whether or not the window OK flag FW3 is 0 (step S512). When FW3 = 0 (step S512: Yes), the viewpoint detection unit 352 sets FW3 = 1 and ends the area A1 process (step S513). If FW3 = 1 already (step S512: No), the area A1 process is terminated.

  In step S514, the viewpoint detection unit 352 determines whether or not there is a gazing point in the window W4 in the area A1 (step S514). When the gazing point is not in W4 (step S514: No), the area A1 process is terminated. When the gazing point is in W4 (step S514: Yes), the process proceeds to step S515. In step S515, the viewpoint detection unit 352 increments the window counter CW4 and sets the current window to W4 (step S515).

  Next, the viewpoint detection unit 352 determines whether or not the window OK flag FW4 is 0 (step S516). When FW4 = 0 (step S516: Yes), FW4 = 1 is set and the area A1 process is terminated (step S517). If FW4 = 1 already (step S516: No), the area A1 process is terminated.

  The area A2 process (step S111), the area A3 process (step S113), and the area A4 process (step S115) are the same as the area A1 process of FIG.

  The flowchart of FIG. 10 is an example, and it is a method that can determine whether a gazing point exists in an area (area counters CA1 to CA4, etc.), whether a gazing point exists in a window (window counters CW1-CW16, etc.), and the like. Any method may be applied as long as it is present. Also, in the case of a configuration in which one diagnostic image is displayed in each area without dividing the area into windows, the same function as described above can be realized by replacing the processing for the window with the processing for the area.

As described above, according to the first embodiment, for example, the following effects can be obtained.
(1) Higher accuracy than conventional devices that have problems with accuracy.
(2) Special glasses are not required and can be used by infants.
(3) It is possible to support not only ADHD but also ASD diagnosis at the same time.

(Second Embodiment)
In the second embodiment, a line-of-sight detection device and a line-of-sight detection method capable of further simplifying the apparatus configuration are realized as compared with the first embodiment.

  Hereinafter, the line-of-sight detection device and the line-of-sight detection method of the second embodiment will be described in detail with reference to the drawings. In addition, this invention is not limited by this embodiment. In the following, an example in which the line-of-sight detection apparatus is used as a diagnosis support apparatus that supports diagnosis of developmental disabilities using the line-of-sight detection result will be described. Applicable devices are not limited to diagnosis support devices.

  The line-of-sight detection apparatus (diagnosis support apparatus) of the present embodiment detects the line of sight using an illumination unit installed at one place. In addition, the line-of-sight detection device (diagnosis support device) of the present embodiment calculates the corneal curvature center position with high accuracy by using a result obtained by gazing at one point on the subject before the line-of-sight detection.

  In addition, an illumination part is an element which can irradiate light to a test subject's eyeball including a light source. The light source is an element that generates light, such as an LED (Light Emitting Diode). A light source may be comprised from one LED, and may be comprised by combining several LED and arrange | positioning in one place. Hereinafter, the “light source” may be used as a term representing the illumination unit in this way.

  FIGS. 11 and 12 are diagrams illustrating an example of the arrangement of the display unit, the stereo camera, the infrared light source, and the subject of the second embodiment. In addition, about the structure similar to 1st Embodiment, the same code | symbol may be attached | subjected and description may be abbreviate | omitted.

  As illustrated in FIG. 11, the diagnosis support apparatus according to the second embodiment includes a display unit 210, a stereo camera 2102, and an LED light source 2103. The stereo camera 2102 is disposed below the display unit 210. The LED light source 2103 is arranged at the center position of two cameras included in the stereo camera 2102. The LED light source 2103 is a light source that irradiates near infrared rays having a wavelength of 850 nm, for example. FIG. 11 shows an example in which an LED light source 2103 (illumination unit) is configured by nine LEDs. Note that the stereo camera 2102 uses a lens that can transmit near-infrared light having a wavelength of 850 nm.

  As shown in FIG. 12, the stereo camera 2102 includes a right camera 2202 and a left camera 2203. The LED light source 2103 irradiates near-infrared light toward the eyeball 111 of the subject. In the image acquired by the stereo camera 2102, the pupil 112 is reflected and darkened with low brightness, and the corneal reflection 113 generated as a virtual image in the eyeball 111 is reflected and brightened with high brightness. Accordingly, the positions of the pupil 112 and the corneal reflection 113 on the image can be acquired by each of the two cameras (the right camera 2202 and the left camera 2203).

  Further, the three-dimensional world coordinate values of the positions of the pupil 112 and the corneal reflection 113 are calculated from the positions of the pupil 112 and the corneal reflection 113 obtained by the two cameras. In the present embodiment, as the three-dimensional world coordinates, with the center position of the display screen 101 as the origin, the top and bottom are the Y coordinate (up is +), the side is the X coordinate (right is +), and the depth is the Z coordinate (front is +).

  FIG. 13 is a diagram illustrating an outline of functions of the diagnosis support apparatus 2100 according to the second embodiment. FIG. 13 shows a part of the configuration shown in FIGS. 11 and 12 and a configuration used for driving the configuration. As illustrated in FIG. 13, the diagnosis support apparatus 2100 includes a right camera 2202, a left camera 2203, an LED light source 2103, a speaker 105, a drive / IF (interface) unit 208, a control unit 2300, and a storage unit 150. And a display unit 210. In FIG. 13, the display screen 101 shows the positional relationship between the right camera 2202 and the left camera 2203 in an easy-to-understand manner, but the display screen 101 is a screen displayed on the display unit 210. The drive unit and the IF unit may be integrated or separate.

  The speaker 105 functions as an audio output unit that outputs an audio or the like for alerting the subject during calibration.

  The drive / IF unit 208 drives each unit included in the stereo camera 2102. The drive / IF unit 208 serves as an interface between each unit included in the stereo camera 2102 and the control unit 2300.

  The control unit 2300 is a communication I / F that communicates with a control device such as a CPU (Central Processing Unit) and a storage device such as a ROM (Read Only Memory) and a RAM (Random Access Memory) by connecting to a network. And a computer equipped with a bus for connecting each unit.

  The storage unit 150 stores various information such as a control program, a measurement result, and a diagnosis support result. The storage unit 150 stores, for example, an image to be displayed on the display unit 210. The display unit 210 displays various information such as a target image for diagnosis.

  FIG. 14 is a block diagram illustrating an example of detailed functions of each unit illustrated in FIG. 13. As shown in FIG. 14, a display unit 210 and a drive / IF unit 208 are connected to the control unit 2300. The drive / IF unit 208 includes camera IFs 314 and 315, an LED drive control unit 316, and a speaker drive unit 322.

  A right camera 2202 and a left camera 2203 are connected to the drive / IF unit 208 via camera IFs 314 and 315, respectively. The driving / IF unit 208 drives these cameras to image the subject.

  The speaker driving unit 322 drives the speaker 105. The diagnosis support apparatus 2100 may include an interface (printer IF) for connecting to a printer as a printing unit. Further, the printer may be provided inside the diagnosis support apparatus 2100.

  The control unit 2300 controls the entire diagnosis support apparatus 2100. The control unit 2300 includes a first calculation unit 2351, a second calculation unit 2352, a third calculation unit 2353, a gaze detection unit 2354, a viewpoint detection unit 2355, an output control unit 2356, and an evaluation unit 2357. I have. Note that the line-of-sight detection device may include at least the first calculation unit 2351, the second calculation unit 2352, the third calculation unit 2353, and the line-of-sight detection unit 2354.

  Each element included in the control unit 2300 (the first calculation unit 2351, the second calculation unit 2352, the third calculation unit 2353, the line-of-sight detection unit 2354, the viewpoint detection unit 2355, the output control unit 2356, and the evaluation unit 2357) It may be realized by software (program), may be realized by a hardware circuit, or may be realized by using software and a hardware circuit in combination.

  When implemented by a program, the program is a file in an installable or executable format, such as a CD-ROM (Compact Disk Read Only Memory), a flexible disk (FD), a CD-R (Compact Disk Recordable), a DVD ( Digital Versatile Disk) is recorded on a computer-readable recording medium and provided as a computer program product. The program may be provided by being stored on a computer connected to a network such as the Internet and downloaded via the network. The program may be provided or distributed via a network such as the Internet. The program may be provided by being incorporated in advance in a ROM or the like.

  The first calculation unit 2351 calculates the position of the pupil center (first position) indicating the center of the pupil from the eyeball image captured by the stereo camera 2102. The second calculator 2352 calculates the position of the corneal reflection center (second position) indicating the center of corneal reflection from the captured image of the eyeball.

  The third calculator 2353 calculates the corneal curvature center (third position) from the straight line connecting the LED light source 2103 and the corneal reflection center. For example, the third calculation unit 2353 calculates a position on the straight line where the distance from the corneal reflection center is a predetermined value as the corneal curvature center. As the predetermined value, a value determined in advance from a general radius of curvature of the cornea or the like can be used.

  Since there may be individual differences in the radius of curvature of the cornea, there is a possibility that an error will increase if the center of corneal curvature is calculated using a predetermined value. Therefore, the third calculation unit 2353 may calculate the corneal curvature center in consideration of individual differences. In this case, the third calculation unit 2353 uses the pupil center and the corneal reflection center calculated when the target position is first watched by the subject, the straight line connecting the pupil center and the target position, the corneal reflection center, and the LED. The intersection (fourth position) of the straight line connecting the light source 2103 is calculated. Then, the third calculation unit 2353 calculates a distance (first distance) between the pupil center and the calculated intersection, and stores it in the storage unit 150, for example.

  The target position may be a position that is determined in advance and can calculate a three-dimensional world coordinate value. For example, the center position of the display screen 101 (the origin of the three-dimensional world coordinates) can be set as the target position. In this case, for example, the output control unit 2356 displays an image (target image) or the like that causes the subject to gaze at the target position (center) on the display screen 101. Thereby, a test subject can be made to gaze at a target position.

  The target image may be any image as long as it can attract the attention of the subject. For example, an image in which a display mode such as luminance or color changes, an image in which the display mode is different from other regions, or the like can be used as the target image.

  The target position is not limited to the center of the display screen 101, and may be an arbitrary position. If the center of the display screen 101 is set as the target position, the distance from an arbitrary end of the display screen 101 is minimized. For this reason, it becomes possible to make the measurement error at the time of gaze detection smaller, for example.

  The processing up to the calculation of the distance is executed in advance, for example, before the actual gaze detection is started. At the time of actual line-of-sight detection, the third calculation unit 2353 calculates, on the straight line connecting the LED light source 2103 and the corneal reflection center, a position where the distance from the pupil center is a previously calculated distance as the corneal curvature center. .

  The line-of-sight detection unit 2354 detects the line of sight of the subject from the pupil center and the corneal curvature center. For example, the gaze detection unit 2354 detects the direction from the corneal curvature center to the pupil center as the gaze direction of the subject.

  The viewpoint detection unit 2355 detects the viewpoint of the subject using the detected gaze direction. The viewpoint detection unit 2355 detects, for example, a viewpoint (gaze point) that is a point on the display screen 101 where the subject gazes. The viewpoint detection unit 2355 detects, for example, the intersection of the line-of-sight vector represented in the three-dimensional world coordinate system as shown in FIG. 12 and the XY plane as the gaze point of the subject.

  The output control unit 2356 controls output of various information to the display unit 210, the speaker 105, and the like. For example, the output control unit 2356 outputs the target image at the target position on the display unit 210. Further, the output control unit 2356 controls the output to the display unit 210 such as the diagnostic image and the evaluation result by the evaluation unit 2357.

  The diagnostic image may be an image corresponding to the evaluation process based on the line-of-sight (viewpoint) detection result. For example, in the case of diagnosing a developmental disorder, a diagnostic image including an image (such as a geometric pattern image) preferred by a subject with a developmental disorder and other images (such as a person image) may be used.

  The evaluation unit 2357 performs an evaluation process based on the diagnostic image and the gazing point detected by the viewpoint detection unit 2355. For example, in the case of diagnosing a developmental disorder, the evaluation unit 2357 analyzes the diagnostic image and the gazing point, and evaluates whether or not the image preferred by the subject with the developmental disorder has been gazed.

  The output control unit 2356 may display the same diagnostic image as that of the first embodiment, and the evaluation unit 2357 may perform the same evaluation process as that of the evaluation unit 354 of the first embodiment. In other words, the gaze detection process (gaze detection unit 351) of the first embodiment is replaced with the gaze detection process (first calculation unit 2351, second calculation unit 2352, third calculation unit 2353, gaze detection of the second embodiment. Part 2354). Thereby, in addition to the effect of 1st Embodiment, the effect (simplification of an apparatus structure etc.) of 2nd Embodiment can be achieved.

  FIG. 15 is a diagram illustrating an outline of processing executed by the diagnosis support apparatus 2100 of this embodiment. The elements described in FIGS. 11 to 14 are denoted by the same reference numerals and description thereof is omitted.

  The pupil center 407 and the corneal reflection center 408 represent the center of the pupil and the center of the corneal reflection point detected when the LED light source 2103 is turned on, respectively. The corneal curvature radius 409 represents the distance from the corneal surface to the corneal curvature center 410.

  FIG. 16 is an explanatory diagram showing a difference between a method using two light sources (illumination units) (hereinafter referred to as method A) and the present embodiment using one light source (illumination unit). The elements described in FIGS. 11 to 14 are denoted by the same reference numerals and description thereof is omitted.

  Method A uses two LED light sources 511 and 512 instead of the LED light source 2103. In the method A, a straight line 515 connecting the cornea reflection center 513 and the LED light source 511 when the LED light source 511 is irradiated, and a straight line 516 connecting the cornea reflection center 514 and the LED light source 512 when the LED light source 512 is irradiated. An intersection is calculated. This intersection is the corneal curvature center 505.

  In contrast, in the present embodiment, a straight line 523 connecting the corneal reflection center 522 and the LED light source 2103 when the LED light source 2103 is irradiated is considered. A straight line 523 passes through the corneal curvature center 505. It is also known that the radius of curvature of the cornea is almost constant with little influence from individual differences. Thus, the corneal curvature center when the LED light source 2103 is irradiated exists on the straight line 523 and can be calculated by using a general curvature radius value.

  However, if the viewpoint is calculated using the position of the center of corneal curvature calculated using a general radius of curvature, the viewpoint position may deviate from the original position due to individual differences in the eyeballs, and accurate viewpoint position detection cannot be performed. There is.

  FIG. 17 is a diagram for explaining calculation processing for calculating the corneal curvature center position and the distance between the pupil center position and the corneal curvature center position before performing viewpoint detection (line-of-sight detection). The elements described in FIGS. 11 to 14 are denoted by the same reference numerals and description thereof is omitted. The connection between the left and right cameras (the right camera 2202 and the left camera 2203) and the control unit 2300 is not shown and is omitted.

  The target position 605 is a position for displaying a target image or the like at one point on the display unit 210 and causing the subject to stare. In this embodiment, the center position of the display screen 101 is set. A straight line 613 is a straight line connecting the LED light source 2103 and the corneal reflection center 612. A straight line 614 is a straight line connecting the target position 605 (gaze point) that the subject looks at and the pupil center 611. A corneal curvature center 615 is an intersection of the straight line 613 and the straight line 614. The third calculation unit 2353 calculates and stores the distance 616 between the pupil center 611 and the corneal curvature center 615.

  FIG. 18 is a flowchart illustrating an example of calculation processing according to the present embodiment.

  First, the output control unit 2356 reproduces the target image at one point on the display screen 101 (step S601), and causes the subject to gaze at the one point. Next, the control unit 2300 turns on the LED light source 2103 toward the eyes of the subject using the LED drive control unit 316 (step S602). The control unit 2300 images the eyes of the subject with the left and right cameras (the right camera 2202 and the left camera 2203) (step S603).

  The pupil part is detected as a dark part (dark pupil) by irradiation of the LED light source 2103. Further, a corneal reflection virtual image is generated as a reflection of LED irradiation, and a corneal reflection point (corneal reflection center) is detected as a bright portion. That is, the first calculation unit 2351 detects a pupil portion from the captured image, and calculates coordinates indicating the position of the pupil center. In addition, the second calculation unit 2352 detects a corneal reflection portion from the captured image, and calculates coordinates indicating the position of the corneal reflection center. The first calculation unit 2351 and the second calculation unit 2352 calculate each coordinate value for each of two images acquired by the left and right cameras (step S604).

  Note that the left and right cameras are pre-calibrated with a stereo calibration method to obtain three-dimensional world coordinates, and conversion parameters are calculated. As the stereo calibration method, any conventionally used method such as a method using Tsai's camera calibration theory can be applied.

  The first calculation unit 2351 and the second calculation unit 2352 use the conversion parameters to convert the coordinates of the left and right cameras into the three-dimensional world coordinates of the pupil center and the corneal reflection center (step S605). The third calculation unit 2353 obtains a straight line connecting the obtained world coordinates of the corneal reflection center and the world coordinates of the center position of the LED light source 2103 (step S606). Next, the third calculation unit 2353 calculates a straight line connecting the world coordinates of the center of the target image displayed at one point on the display screen 101 and the world coordinates of the pupil center (step S607). The 3rd calculation part 2353 calculates | requires the intersection of the straight line calculated by step S606, and the straight line calculated by step S607, and makes this intersection a cornea curvature center (step S608). The third calculation unit 2353 calculates the distance between the pupil center and the corneal curvature center at this time and stores it in the storage unit 150 or the like (step S609). The stored distance is used to calculate the corneal curvature center at the time of subsequent detection of the viewpoint (line of sight).

  The distance between the pupil center and the corneal curvature center when looking at one point on the display unit 210 in the calculation process is kept constant within a range in which the viewpoint in the display unit 210 is detected. The distance between the center of the pupil and the center of corneal curvature may be obtained from the average of all the values calculated during playback of the target image, or from the average of several values of the values calculated during playback. You may ask for it.

  FIG. 19 is a diagram illustrating a method of calculating the corrected position of the corneal curvature center using the distance between the pupil center and the corneal curvature center that is obtained in advance when performing viewpoint detection. A gazing point 805 represents a gazing point obtained from a corneal curvature center calculated using a general curvature radius value. A gazing point 806 represents a gazing point obtained from a corneal curvature center calculated using a distance obtained in advance.

  The pupil center 811 and the corneal reflection center 812 indicate the position of the pupil center and the position of the corneal reflection center calculated at the time of viewpoint detection, respectively. A straight line 813 is a straight line connecting the LED light source 2103 and the corneal reflection center 812. The corneal curvature center 814 is the position of the corneal curvature center calculated from a general curvature radius value. The distance 815 is the distance between the pupil center and the corneal curvature center calculated by the prior calculation process. The corneal curvature center 816 is the position of the corneal curvature center calculated using the distance obtained in advance. The corneal curvature center 816 is obtained from the fact that the corneal curvature center exists on the straight line 813 and the distance between the pupil center and the corneal curvature center is the distance 815. Thus, the line of sight 817 calculated when a general radius of curvature value is used is corrected to the line of sight 818. Also, the gazing point on the display screen 101 is corrected from the gazing point 805 to the gazing point 806. The connection between the left and right cameras (the right camera 2202 and the left camera 2203) and the control unit 2300 is not shown and is omitted.

  FIG. 20 is a flowchart illustrating an example of a line-of-sight detection process according to the present embodiment. For example, the line-of-sight detection process of FIG. 20 can be executed as the process of detecting the line of sight in the diagnostic process using the diagnostic image. In the diagnostic process, in addition to the steps in FIG. 20, a process of displaying a diagnostic image, an evaluation process by the evaluation unit 2357 using the detection result of the gazing point, and the like are executed.

  Steps S701 to S705 are the same as steps S602 to S606 in FIG.

  The third calculation unit 2353 calculates, as the corneal curvature center, a position on the straight line calculated in step S705 and whose distance from the pupil center is equal to the distance obtained by the previous calculation process (step S706).

  The line-of-sight detection unit 2354 obtains a vector (line-of-sight vector) connecting the pupil center and the corneal curvature center (step S707). This vector indicates the line-of-sight direction viewed by the subject. The viewpoint detection unit 2355 calculates the three-dimensional world coordinate value of the intersection between the line-of-sight direction and the display screen 101 (step S708). This value is a coordinate value representing one point on the display unit 210 that the subject gazes in world coordinates. The viewpoint detection unit 2355 converts the obtained three-dimensional world coordinate value into a coordinate value (x, y) represented in the two-dimensional coordinate system of the display unit 210 (step S709). Thereby, the viewpoint (gaze point) on the display part 210 which a test subject looks at can be calculated.

As described above, according to the present embodiment, for example, the following effects can be obtained.
(1) It is not necessary to arrange light sources (illuminating units) at two places, and it becomes possible to perform line-of-sight detection with the light sources arranged at one place.
(2) Since the number of light sources is one, the apparatus can be made compact and the cost can be reduced.

100, 2100 Diagnosis support device 101 Display screen 102, 2101 Stereo camera 105 Speaker 150 Storage unit 202, 2202 Right camera 203 Infrared LED light source 204, 2203 Left camera 205 Infrared LED light source 208 Drive / IF unit 210 Display unit 300, 2300 Control unit 351, 2354 Gaze detection unit 352, 2355 View point detection unit 353, 2356 Output control unit 354, 2357 Evaluation unit 2351 First calculation unit 2352 Second calculation unit 2353 Third calculation unit

Claims (7)

A display unit;
An imaging unit for imaging a subject;
From a captured image captured by the imaging unit, a gaze detection unit that detects the gaze direction of the subject,
A viewpoint detection unit that detects the viewpoint of the subject in a plurality of divided areas obtained by dividing the display area of the display unit based on the line-of-sight direction;
An output control unit that displays at least two of a person image, a pattern image, and a character image as diagnostic images in different divided areas among the divided areas;
An evaluation unit that calculates an evaluation value of the subject based on the viewpoint detected by the viewpoint detection unit when the diagnostic image is displayed;
A diagnostic support apparatus comprising: The evaluation unit includes a movement distance of the viewpoint within a predetermined period, a movement speed of the viewpoint within the predetermined period, a number of the viewpoints detected in the divided areas within the predetermined period, and a predetermined period. Calculating the evaluation value based on at least one of the number of times the viewpoint has moved between the plurality of divided regions;
The diagnosis support apparatus according to claim 1. The divided region includes a plurality of partial regions,
The evaluation unit is based on at least one of the number of the viewpoints detected in the partial area within the predetermined period and the number of times the viewpoint has moved between the plurality of partial areas within the predetermined period. Calculating an evaluation value,
The diagnosis support apparatus according to claim 1. The evaluation unit calculates the evaluation value based on a time when the viewpoint is detected in a divided region including the pattern image and a time when the viewpoint is detected in a region other than the divided region including the pattern image;
The diagnosis support apparatus according to claim 1. The output control unit changes the divided area for displaying the diagnostic image in the first period and the second period,
The evaluation unit calculates the evaluation value based on a first evaluation value calculated in the first period and a second evaluation value calculated in the second period;
The diagnosis support apparatus according to claim 1. An illumination unit including a light source that emits light;
A first calculation unit that calculates a first position indicating the center of the pupil from an image of the eyeball of the subject that is illuminated by the illumination unit and imaged by the imaging unit;
A second calculation unit that calculates a second position indicating the center of corneal reflection from the captured image of the eyeball;
A third calculator that calculates a third position indicating a corneal curvature center based on a straight line connecting the light source and the second position;
The line-of-sight detection unit detects the line of sight of the subject based on the first position and the third position;
The diagnosis support apparatus according to claim 1. A line-of-sight detection step for detecting a line-of-sight direction of the subject from a captured image captured by an imaging unit that images the subject,
A viewpoint detection step of detecting the viewpoint of the subject in a plurality of divided areas obtained by dividing the display area of the display unit based on the line-of-sight direction;
An output control step of displaying at least two of a person image, a pattern image, and a character image as diagnostic images in different divided areas among the divided areas;
An evaluation step of calculating an evaluation value of the subject based on the viewpoint detected by the viewpoint detection step when the diagnostic image is displayed;
A diagnostic support method including: