A dynamic stereoscopic vision detection system

Abstract

The present invention relates to the field of visual detection technology, and specifically provides a dynamic stereoscopic visual detection system, including a display module, a processing module and a user interaction module that are interconnected, wherein the display module is used to display a stereoscopic image for detection, and the display module displays a dynamic stereoscopic detection image, including a left-eye image and a right-eye image, and there is a pixel difference between the two. The detected person feeds back the observed information to the processing module through the user interaction module, and the processing module includes an analysis and judgment unit and a control and adjustment unit. The analysis and judgment unit can judge the correctness of the feedback information of the detected person, and the control and adjustment unit selects a suitable adjustment difference to adjust the pixel difference based on the feedback information of the detected person and the feedback duration of the detected person. The present invention can quickly locate the pixel difference interval that the detected person can actually identify by setting the pixel difference adjustment method, and refine the detection within this interval to accurately output the final value.

Description

Technical Field

[0001] The invention relates to the technical field of visual detection, and specifically provides a dynamic stereoscopic visual detection system. Background Art

[0002] Stereoscopic vision, also known as depth perception, refers to the brain's ability to perceive the position and depth of objects in three-dimensional space by integrating information from both eyes. The normal operation of stereoscopic vision depends on the coordinated work between the eyes and the brain, including binocular alignment, focusing, image transmission and brain processing.

[0003] Stereoscopic vision is measured using a deep motion stereo test image. The pixel differences between the test left image and the test right image, as well as between the control left image and the control right image, can be adjusted to create test images of different difficulty levels. A larger pixel difference represents a lower difficulty, and a smaller pixel difference represents a higher difficulty. The current pixel difference adjustment method mostly uses a linear decrease method. In each test iteration, the pixel difference decreases by a fixed value. If the initial pixel difference decrease value is set too large, the subject's accurate threshold range may be missed. If the initial pixel difference decrease value is set too small, the number of tests may increase, wasting time and increasing the subject's fatigue. Summary of the invention

[0004] In view of the above-mentioned defects, the present invention provides a dynamic stereoscopic vision detection system, the purpose of which is to solve the problem that the pixel difference adjustment method is difficult to set in the prior art.

[0005] In order to achieve the above-mentioned purpose, the present invention provides a dynamic stereoscopic vision detection system, which includes a display module, a processing module and a user interaction module that are interconnected. The display module is used to display a stereoscopic image for detection. The display module displays a dynamic stereoscopic detection image, including a left-eye image and a right-eye image, and there is a pixel difference between the two. The person being tested feeds back the observed information to the processing module through the user interaction module. It is characterized in that the processing module includes an analysis and judgment unit and a control and adjustment unit. The analysis and judgment unit can judge the correctness of the feedback information of the person being tested, and the control and adjustment unit selects a suitable adjustment difference to adjust the pixel difference based on the feedback information of the person being tested and the feedback duration of the person being tested.

[0006] Preferably, the method comprises the following steps:

[0007] S1. The subject sits on the test chair facing the display screen and takes the test;

[0008] S2, the image processing module controls the display screen to display the image required for detection, and the person being detected feeds back the information he or she has identified through the interactive module;

[0009] S3, starting from the system default maximum threshold pixel difference d1, the processing module determines the observation result according to the feedback information of the person being tested and adjusts the pixel difference of the image displayed on the next display screen to d n Until the subject gives back the wrong result and then gives back the correct result, the pixel difference d is recorded when the subject gives back the wrong result for the last time. z1 The first round is over.

[0010] Preferably, in step S3, the pixel difference adjustment method is: n =d n-1 -A*k i ;

[0011] Where A is the discriminant factor. If the feedback information of the subject is correct, A = 1; if the feedback information of the subject is incorrect, A = -1;

[0012] d1 is the initial pixel difference, k i is the adjustment difference, k i =[k1, k2, k3, k4], and k1>k2>k3>k4, the control and adjustment unit calculates △T=T n -T0, the control and adjustment unit presets △T1, △T2, △T3 and △T1<△T2<△T3,

[0013] Among them, T n is the feedback duration of the subject, T0 is the preset feedback duration of the subject;

[0014] If the test subject's feedback is correct,

[0015] When △T<△T1, the control and adjustment unit uses the adjustment difference k1 to adjust the adjustment difference;

[0016] When △T1≤△T<△T2, the control and adjustment unit uses the adjustment difference k2 to adjust the adjustment difference;

[0017] When △T≥△T2, the control and adjustment unit adopts the adjustment difference k3 to adjust the adjustment difference;

[0018] If the measured person's feedback information is wrong, the control adjustment unit adopts the adjustment difference k4 to adjust the adjustment difference.

[0019] Preferably, the method further comprises the following steps:

[0020] S4, start the i-th round of testing, i is the number of testing rounds, the initial pixel difference di0 of the i-th round of testing = d z1 +K4 / 2, the processing module determines the observation result according to the feedback information of the person being tested and adjusts the pixel difference of the image displayed on the next display screen to di nUntil the subject gives back the wrong result and then gives back the correct result, the pixel difference d is recorded when the subject gives back the wrong result for the last time. zi This round is over;

[0021] S5. Repeat step S4.

[0022] Preferably, in step S4, the pixel difference is adjusted as follows: n =di n-1 -A*k4.

[0023] Preferably, T0 is obtained in the following manner:

[0024] A1. The subject sits on the test chair facing the display screen for pre-test;

[0025] A2. The image processing module controls the display screen to display the image required for detection, and the person being detected feeds back the information he or she has identified through the interactive module;

[0026] A3. The pre-test uses the maximum threshold pixel difference to ensure that the subject can easily identify the stereo depth. The subject is tested multiple times in a row, and the recognition feedback time of each subject is recorded to calculate the average value T0.

[0027] Preferably, it also includes a collection module, which is electrically connected to the processing module, and the collection module includes a number of biological signal sensors for detecting the heart rate and breathing rate of the subject;

[0028] The processing module also includes a data recording unit and a data processing unit connected to each other.

[0029] The data recording unit is used to integrate the sensor data and the pixel difference data. The data processing unit can be used to calculate the pixel difference d according to the current round of testing. zi The sharpness value Ri of each round of measurement is calculated based on the average heart rate Xi and breathing rate Xi of the subject during each round of testing.

[0030] Preferably, the sharpness value is calculated as Ri=[206280*E*(d zi +K4) / (N*L)+α*(Xi-X0)+β*(Yi-Y0); calculate the sharpness value of each round of test and take the average value as the final test result;

[0031] Wherein, E is the area of ​​the display screen, N is the number of pixels of the display screen, L is the distance from the observer to the display screen, α is the first adjustment factor, β is the second adjustment factor, X0 is the heart rate of the subject under normal conditions, and Y0 is the breathing rate of the subject under normal conditions.

[0032] The object of the present invention is to provide a dynamic stereoscopic vision detection system, which has the following beneficial effects:

[0033] The present invention can quickly locate the pixel difference interval that the subject can actually identify by setting the pixel difference adjustment mode, and refine the detection within this interval to accurately output the final value, so that the number of tests is within a smaller range and accurate pixel differences are obtained under the premise of minimizing the fatigue of the subject. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a schematic diagram of a dynamic stereoscopic vision detection system. DETAILED DESCRIPTION

[0035] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0036] The present invention provides a dynamic stereoscopic vision detection system, comprising a display module, a processing module and a user interaction module that are interconnected. The display module is used to display a stereoscopic image for detection. The display module displays a dynamic stereoscopic detection image, including a left-eye image and a right-eye image. The left eye of a person being detected can only observe a dynamic stereoscopic vision left image, and the right eye can only observe a dynamic stereoscopic vision right image, and there is a pixel difference between the two. The person being detected feeds back the observed information to the processing module through the user interaction module. The system is characterized in that the processing module comprises an analysis and judgment unit and a control and adjustment unit. The analysis and judgment unit can judge the correctness of the feedback information of the person being detected, and the control and adjustment unit selects a suitable adjustment difference to adjust the pixel difference based on the feedback information of the person being detected and the feedback duration of the person being detected.

[0037] Specifically, the display module displays four groups of images simultaneously, including a group of motion perception test images and three groups of motion perception control images. The motion directions of the three groups of motion perception control images are the same and different from the motion direction of the group of motion perception test images. The subject distinguishes the group of images with different motion directions from the four groups of images.

[0038] When the pixel difference decreases, the motion depth of the four groups of motion images will decrease accordingly, and the difficulty for the subjects to distinguish the different groups of images will increase accordingly.

[0039] Specifically, the interactive module may be a testing chair for the tested person to sit on and buttons installed on the armrests of the testing chair, and the number of buttons is consistent with the number of images.

[0040] It includes the following steps:

[0041] Conduct the first round of testing.

[0042] S1. The subject sits on the test chair and faces the display screen for testing. Ensure that the subject is in the correct position, facing the display screen, ensure the consistency and repeatability of the test environment, and reduce interference from external factors.

[0043] S2, the image processing module controls the display screen to display the image required for detection, and the person being detected feeds back the information he or she has identified through the interactive module;

[0044] S3, starting from the system default maximum threshold pixel difference d1, the processing module determines the observation result according to the feedback information of the tested person and adjusts the pixel difference of the next display screen image test group to d n Until the subject gives back the wrong result and then gives back the correct result, the pixel difference d is recorded when the subject gives back the wrong result for the last time. z1 The first round is over. This step finds the recognition limit of the subject by gradually reducing the pixel difference.

[0045] As a further explanation of this embodiment, in step S3, the pixel difference adjustment method is: n =d n-1 -A*k i ;

[0046] Where A is the discriminant factor. If the feedback information of the subject is correct, A = 1; if the feedback information of the subject is incorrect, A = -1;

[0047] d1 is the initial pixel difference, k i is the adjustment difference, k i =[k1, k2, k3, k4], and k1>k2>k3>k4, the control and adjustment unit calculates △T=T n -T0, the control and adjustment unit presets △T1, △T2, △T3 and △T1<△T2<△T3,

[0048] Among them, T n is the feedback duration of the subject, T0 is the preset feedback duration of the subject;

[0049] If the test subject's feedback is correct,

[0050] When △T<△T1, the control and adjustment unit uses the adjustment difference k1 to adjust the adjustment difference;

[0051] When △T1≤△T<△T2, the control and adjustment unit uses the adjustment difference k2 to adjust the adjustment difference;

[0052] When △T≥△T2, the control and adjustment unit adopts the adjustment difference k3 to adjust the adjustment difference;

[0053] If the measured person's feedback information is wrong, the control adjustment unit adopts the adjustment difference k4 to adjust the adjustment difference.

[0054] Because the pixel difference is large at the beginning, it is easy for the test subject to select the correct image and the time taken is short. Therefore, a larger adjustment difference is selected to quickly reduce the pixel difference and increase the test difficulty. As the test subject's time increases, it proves that it is difficult for him to quickly determine the correct image. In this case, it is necessary to reduce the adjustment difference and gradually approach the pixel difference that the test subject can actually identify. When the test subject gives back the wrong information, it proves that the test subject can no longer distinguish the correct image under the current pixel difference test environment. At this time, it is necessary to use the smallest adjustment difference to slowly increase the pixel difference and accurately approach the pixel difference that the test subject can actually identify. When the test subject reselects the correct image, the actual pixel difference should be between the pixel difference when the test subject last gave back the wrong result and the pixel difference of the correct image fed back this time.

[0055] This pixel difference adjustment method can quickly locate the pixel difference range that the subject can actually recognize, and refine the detection within this range to accurately determine the final output value.

[0056] As a further explanation of this embodiment, a subsequent test is also included, the steps of which are:

[0057] S4, start the i-th round of testing, i is the number of testing rounds, the initial pixel difference di0 of the i-th round of testing = d z1 +K4 / 2, the processing module determines the observation result according to the feedback information of the person being tested and adjusts the pixel difference of the image displayed on the next display screen to di n Until the subject gives back the wrong result and then gives back the correct result, the pixel difference d is recorded when the subject gives back the wrong result for the last time. zi This round is over;

[0058] S5. Repeat step S4.

[0059] As a further explanation of this embodiment, in step S4, the pixel difference is adjusted as follows: n =di n-1 -A*k4.

[0060] Because the test itself is accidental, multiple rounds of testing are required. Because the first group has determined the pixel difference range that the subjects can recognize, the subsequent tests can start directly with the median of this range, and the smallest k4 is selected for adjusting the difference.

[0061] As a further explanation of this embodiment, T0 is obtained as follows:

[0062] A1. The subject sits on the test chair facing the display screen for pre-test;

[0063] A2. The image processing module controls the display screen to display the image required for detection, and the person being detected feeds back the information he or she has identified through the interactive module;

[0064] A3. The pre-test uses the maximum threshold pixel difference to ensure that the subject can easily identify the stereo depth. The subject is tested multiple times in a row, and the recognition feedback time of each subject is recorded to calculate the average value T0.

[0065] As a further explanation of this embodiment, it is characterized in that it also includes a collection module, which is electrically connected to the processing module, and the collection module includes a plurality of biological signal sensors, including at least one heart rate sensor and at least one respiratory rate sensor, for detecting the heart rate and respiratory rate of the subject to be tested;

[0066] The processing module also includes a data recording unit and a data processing unit which are connected to each other.

[0067] The data recording unit is used to integrate the sensor data and the pixel difference data. The data processing unit can be used to calculate the pixel difference d according to the current round of testing. zi The sharpness value Ri of each round of measurement is calculated based on the average heart rate Xi and breathing rate Xi of the subject during each round of testing.

[0068] As a further explanation of this embodiment, the sharpness value is calculated as Ri=[206280*E*(d zi +K4) / (N*L)+α*(Xi-X0)+β*(Yi-Y0); calculate the sharpness value of each round of test and take the average value as the final test result;

[0069] Wherein, E is the area of ​​the display screen, N is the number of pixels of the display screen, L is the distance from the observer to the display screen, α is the first adjustment factor, β is the second adjustment factor, X0 is the heart rate of the subject under normal conditions, and Y0 is the breathing rate of the subject under normal conditions.

[0070] The first adjustment factor α and the second adjustment factor β can be calculated through previous measurement data.

[0071] The sharpness value calculation method of the present invention refers to the calculation method of the Chinese invention patent with application number 202011267053.1, and on this basis, takes into account the influence of the state of the subject on the test result and makes corrections to the final output value.

[0072] The present invention is not limited to the above-mentioned specific implementation modes. Various changes made by ordinary technicians in this field based on the above-mentioned concepts without creative work are all within the protection scope of the present invention.

Claims

1. A dynamic stereoscopic vision detection system, comprising a display module, a processing module and a user interaction module connected to each other, wherein the display module is used to display a stereoscopic image for detection, and the display module displays a dynamic stereoscopic detection image, including a left-eye image and a right-eye image, with pixel differences between the two. The detected person feeds back the observed information to the processing module through the user interaction module, characterized in that: The processing module includes an analysis and determination unit and a control and adjustment unit, wherein the analysis and determination unit can determine the correctness of the feedback information of the subject, and the control and adjustment unit selects a suitable adjustment difference value to adjust the pixel difference based on the feedback information of the subject and the feedback duration of the subject; The steps include: S1. The subject sits on the test chair facing the display screen and takes the test; S2, the image processing module controls the display screen to display the image required for detection, and the person being detected feeds back the information he or she has identified through the interactive module; S3, starting from the system default maximum threshold pixel difference d1, the processing module determines the observation result according to the feedback information of the person being tested and adjusts the pixel difference of the image displayed on the next display screen to d n Until the subject gives back the wrong result and then gives back the correct result, the pixel difference d is recorded when the subject gives back the wrong result for the last time. z1 The first round is over; The pixel difference adjustment method is: d n =d n-1 -A*k i ; Where A is the discriminant factor. If the feedback information of the subject is correct, A=1; if the feedback information of the subject is incorrect, A=-1; d1 is the initial pixel difference, k i is the adjustment difference, k i =[k1,k2,k3,k4], and k1>k2>k3>k4, The control and adjustment unit calculates △T=T n -T0, the control and adjustment unit presets △T1, △T2, △T3 and △T1<△T2<△T3, Among them, T n is the feedback duration of the subject, T0 is the preset feedback duration of the subject; If the test subject's feedback is correct, When △T<△T1, the control adjustment unit takes the adjustment difference k1 to adjust the adjustment difference; When △T1≤△T<△T2, the control adjustment unit adopts the adjustment difference k2 to adjust the adjustment difference; When △T≥△T2, the control adjustment unit takes the adjustment difference k3 to adjust the adjustment difference; If the feedback information from the subject is wrong, the control adjustment unit is used to adjust the adjustment difference by adopting the adjustment difference k4; S4, start the i-th round of testing, i is the number of testing rounds, the initial pixel difference di0 of the i-th round of testing = d z1 +K4 / 2, the processing module determines the observation result according to the feedback information of the person being tested and adjusts the pixel difference of the image displayed on the next display screen to di n Until the subject gives back the wrong result and then gives back the correct result, the pixel difference d is recorded when the subject gives back the wrong result for the last time. zi This round is over; S5, repeat step S4; It also includes a collection module, which is electrically connected to the processing module, and the collection module includes a number of biological signal sensors for detecting the heart rate and breathing rate of the subject to be tested; The processing module also includes a data recording unit and a data processing unit connected to each other. The data recording unit is used to integrate the sensor data and the pixel difference data. The data processing unit can zi The sharpness value Ri of each round of measurement is calculated based on the average heart rate Xi and breathing rate Yi of the subject during each round of testing; The sharpness value is calculated as Ri=[206280*E*(d zi +K4) / (N*L)+α*(Xi-X0)+β*(Yi-Y0); calculate the sharpness value of each round of test and take the average value as the final test result; Where, E is the area of ​​the display screen, N is the number of pixels of the display screen, and L is the distance from the observer to the display screen. α is the first adjustment factor, β is the second adjustment factor, X0 is the heart rate of the subject under normal conditions, and Y0 is the breathing rate of the subject under normal conditions.

2. The dynamic stereoscopic vision detection system according to claim 1, characterized in that: In step S4, the pixel difference is adjusted as follows: n =di n-1 -A*k4.

3. The dynamic stereoscopic vision detection system according to claim 2, characterized in that: T0 is obtained as follows: A1. The subject sits on the test chair facing the display screen for pre-test; A2. The image processing module controls the display screen to display the image required for detection, and the person being detected feeds back the information he or she has identified through the interactive module; A3. The pre-test uses the maximum threshold pixel difference to ensure that the subject can easily identify the stereo depth. The subject is tested multiple times in a row, and the recognition feedback time of each subject is recorded to calculate the average value T0.

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