Education tablet system with management and control function

Abstract

The invention relates to the field of education tablets, in particular to an education tablet system with a management and control function, which is provided with a binocular detection module, an action analysis module, a switching analysis module, a feature analysis module and a management and control module, and analyzes gaze action features by acquiring image data of a detection target. Dividing the current gazing action category of the detection target, and under the strong gazing action category, judging whether the visual stimulation standard is met or not according to the difference of the visual image features in the current browsing page and the pre-switching browsing page, so as to optimize the pre-switching browsing page, the visual influence parameter is calculated based on the pupil change characteristics in the visual stimulated time domain so as to correspondingly send out a control prompt, the gazing action characteristics of the detection target can be obtained, the situation of stimulation to the visual sense in the page switching process can be found in time and intervened in time, the control prompt is sent out in time, and the user experience is improved. The stimulation and influence on vision are reduced, and the use experience of a user is improved.

Description

Technical Field

[0001] The present invention relates to the field of educational tablets, and in particular to an educational tablet system with a management and control function. Background Art

[0002] With the advancement of educational informatization and digital transformation, the functions and experience of educational tablets have been continuously upgraded, and the number of users has increased. Especially in the field of children's education, educational tablets are widely used. However, educational tablets also need to consider the user's addiction, vision damage and other aspects during use, and certain management and control functions need to be set up.

[0003] Chinese patent publication number: CN117555509A, discloses a screen adjustment method, system, device and medium for an educational tablet computer, including a screen adjustment method, system, device and medium for an educational tablet computer, wherein the system extracts characteristic points of an eye image to extract the coordinates of the eye characteristic points; then the system obtains the camera distortion parameter, performs distortion correction on the eye characteristic point coordinates, and then calculates the actual distance of the target. The system measures the brightness value of the current environment through the light sensor of the tablet computer. The system calculates the required blue light filtering intensity based on the calculated current environment brightness value and the actual distance of the target. The system automatically adjusts the display parameters such as the brightness, contrast and color temperature of the tablet computer screen according to the blue light filtering intensity. By correcting the eye characteristic point coordinates, more realistic eye characteristic point coordinates are ensured. In order to obtain the actual distance of the target, the distance measurement error caused by camera distortion is reduced, and the blue light adjustment based on the distance from the eye to the screen is ensured to be more accurate. The accuracy of the screen blue light adjustment is improved to protect eyesight.

[0004] However, there are still the following problems in the prior art:

[0005] In the prior art, when a user focuses on the screen, the user will adapt to the image features of the current page due to the adaptation mechanism of the human eye. However, when switching pages, if the image parameters between the switched pages are significantly different, it may cause visual stimulation and affect vision. Summary of the invention

[0006] To this end, the present invention provides an educational tablet system with a management and control function, which is used to overcome the problem in the prior art that when the user focuses more on the screen, the user will adapt to the image characteristics of the current page due to the adaptation mechanism of the human eye, but when switching pages, if the image parameters between the switched pages are very different, it may cause visual stimulation and affect vision.

[0007] To achieve the above-mentioned object, the present invention provides an educational tablet system with a management and control function, including a binocular detection module, which is arranged on the educational tablet to obtain image data of a detection target;

[0008] An action analysis module, which is connected to the binocular detection module, is used to analyze the gaze action characteristics of the detection target based on the image data, calculate the visual concentration characterization parameter according to the gaze action characteristics, and classify the current gaze action category of the detection target;

[0009] A switching analysis module connected to the action analysis module, in response to the division result of the action analysis module, determines whether the pre-switching browsing page meets the visual stimulation standard according to the difference in visual image features between the current browsing page and the pre-switching browsing page, so as to optimize the pre-switching browsing page;

[0010] a feature analysis module, which is connected to the binocular detection module and the switching analysis module respectively, and is used to respond to the page switching moment, determine the visual stimulation time domain segment according to the page switching moment, and call the image data of the detection target in the visual stimulation time domain segment to analyze the pupil change characteristics;

[0011] A control module, which is connected to the feature analysis module, and is used to calculate visual impact parameters based on the pupil change features combined with the visual image features of the browsing page after switching, and determine whether to issue a control prompt;

[0012] The gaze action features include gaze vector deviation angle, facial gaze distance and gaze vector change frequency, and the visual image features include color quantity and color saturation mean.

[0013] Furthermore, the action analysis module is used to analyze and detect the gaze action features of the target based on the image data, including:

[0014] It is used to determine the facial reference plane of the monitoring target in the image data, and select any eye reference point in the facial reference plane to construct the normal vector of the facial reference plane as the gaze vector;

[0015] The angle between the gaze vector and the normal vector of the plane where the educational tablet is located is determined as the gaze vector offset angle;

[0016] Determine the distance between the center of the facial reference plane and a predetermined reference point as the facial gaze distance;

[0017] The number of changes in the direction of the gaze vector within the reference time is used to determine the frequency of the gaze vector change;

[0018] The facial reference plane is a plane formed by two eye reference points and a forehead reference point, and the predetermined reference point is the center of the educational flat panel display screen.

[0019] Furthermore, the action analysis module is used to calculate the visual focus characterization parameter based on the gaze action feature, including:

[0020] Determining the ratio of the gaze vector deviation angle to a preset standard gaze vector deviation angle standard threshold as the first visual focus influencing factor;

[0021] The ratio of the facial gaze distance to a preset facial gaze distance standard threshold is used to determine the second vision concentration influencing factor;

[0022] for determining the ratio of the gaze vector change frequency to a preset gaze vector change frequency standard threshold as the third visual focus influencing factor;

[0023] The first vision concentration influencing factor, the second vision concentration influencing factor and the third vision concentration influencing factor are weighted and summed to obtain a vision concentration characterization parameter.

[0024] Furthermore, the action analysis module divides the current gaze action category of the monitoring target into:

[0025] If the visual concentration characterization parameter is within a preset visual concentration characterization parameter interval, classifying the gaze action category as a strong gaze action category;

[0026] If the visual concentration characterization parameter is not within the preset visual concentration characterization parameter interval, the gaze action category is classified as a weak gaze action category.

[0027] Furthermore, the handover analysis module responds to the division result of the action analysis module by:

[0028] If the action analysis module classifies the gaze action category as a strong gaze action category, the action analysis module is started.

[0029] Furthermore, the switching analysis module is used to determine whether the pre-switching browsing page meets the visual stimulation standard and optimize the pre-switching browsing page, wherein:

[0030] for respectively determining a color quantity difference ratio and a color saturation mean value difference ratio between a browsing page and a pre-switched browsing page;

[0031] for determining the sum of the color quantity difference ratio and the color saturation difference ratio as the difference;

[0032] If the difference is greater than or equal to a preset difference threshold, the switching analysis module determines that the pre-switching browsing page does not meet the visual stimulation standard, and the pre-switching browsing page is optimized;

[0033] Among them, the optimization includes reducing the color saturation of each area of ​​the pre-switch browsing page.

[0034] Furthermore, the feature analysis module determines a time domain segment corresponding to a predetermined time after a page switching moment as a visually stimulated time domain segment.

[0035] Furthermore, the feature analysis module is used to call the image data of the detected target in the visual stimulation time domain to analyze the pupil change characteristics, including:

[0036] Used to mark the pupil contour in each frame of image data and determine the maximum contour spacing of the pupil contour;

[0037] It is used to calculate the change amplitude of the maximum contour spacing in the visual stimulation time domain segment, and determine the change amplitude as the pupil change feature.

[0038] Furthermore, the control module is used to calculate visual impact parameters.

[0039] The ratio of the color quantity to the preset color quantity standard threshold is used to calculate the first visual impact factor;

[0040] The ratio of the color saturation mean value to the preset color saturation standard threshold value is used to calculate the second visual impact factor;

[0041] Used to determine the sum of the first visual impact factor and the second visual impact factor as a visual impact parameter.

[0042] Furthermore, the control module determines whether to issue a control prompt including:

[0043] If the visual impact parameter is greater than a preset visual impact parameter threshold, it is determined to issue a control prompt.

[0044] Compared with the prior art, the present invention sets a binocular detection module, a motion analysis module, a switching analysis module, a feature analysis module and a control module, analyzes the gaze action features by acquiring the image data of the detection target, calculates the visual concentration characterization parameters, and divides the current gaze action category of the detection target. Under the strong gaze action category, according to the difference in visual image features between the current browsing page and the pre-switching browsing page, it is determined whether the pre-switching browsing page meets the visual stimulation standard, so as to optimize the pre-switching browsing page. Subsequently, the visual impact parameters are calculated based on the pupil change characteristics in the visually stimulated time domain segment combined with the visual image characteristics, so as to issue corresponding control prompts. The present invention can obtain the gaze action features of the detection target, promptly discover the situation that causes visual stimulation during the page switching process and intervene in time, and issue control prompts in time, so as to reduce the stimulation and impact on the vision and improve the user experience.

[0045] In particular, the present invention calculates visual focus characterization parameters and divides the current gaze action category of the detection target. In actual situations, when the user focuses on the screen, the action dimension and the eye feature dimension have data characterization. Therefore, the present invention extracts gaze action features, including gaze vector offset angle, facial gaze distance and gaze vector change frequency. The gaze vector offset angle is used to characterize whether the gaze direction is focused on the screen. The facial gaze distance can simply and reliably characterize whether a gaze action occurs. The gaze vector change frequency is used to characterize the degree of gaze concentration, and then the visual focus characterization parameters are calculated to characterize the degree of gaze of the detection target on the screen, providing data support for the classification of gaze action categories, so as to facilitate the subsequent timely calling of the switching analysis module, evaluate whether it meets the visual stimulation labeling, optimize the pre-switching page, and thus reduce the visual stimulation and influence during the use of the educational tablet, and improve the user experience.

[0046] In particular, the segmentation analysis module of the present invention responds to the division results of the action analysis module. In actual situations, under relatively concentrated gaze, due to the adaptation mechanism of the human eye, it will relatively adapt to the visual image characteristics of the current browsing page, such as color saturation, etc. The use of educational tablets usually involves page switching. If there is a large difference between the pre-switching page and the current switching page, it will cause stimulation to the eye vision. Therefore, after dividing the gaze action category of the detection target, the present invention promptly analyzes the browsing page through the switching analysis module, and then intervenes in time to optimize the pre-switching browsing page. Therefore, it can reduce the visual stimulation and influence during the use of the educational tablet and improve the user experience.

[0047] In particular, the feature analysis module of the present invention calls the image data within the visual stimulation time domain to analyze the pupil change characteristics. In actual situations, the pupil of the human eye will change after being stimulated. Therefore, the pupil change characteristics within the visual stimulation time domain are monitored, and the visual image characteristics of the browsing page after switching are analyzed. Considering whether there is a high degree of eye irritation in the browsing page after switching, and then issuing control prompts in time, reducing the visual stimulation and influence during the use of the educational tablet, and improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 This is a schematic diagram of the structure of an educational tablet system with management and control functions according to an embodiment of the invention;

[0049] Figure 2 A logic block diagram for classifying the current gaze action category of a detection target according to an embodiment of the invention;

[0050] Figure 3 A logic block diagram of an embodiment of the invention for determining whether a pre-switched browsing page meets the visual stimulation standard;

[0051] Figure 4 A logic block diagram for determining whether to issue a control prompt according to an embodiment of the present invention. DETAILED DESCRIPTION

[0052] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; 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.

[0053] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0054] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0055] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the term "connection" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be an indirect connection through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0056] See also Figures 1 to 4 As shown, Figure 1 This is a schematic diagram of the structure of an educational tablet system with management and control functions according to an embodiment of the invention. Figure 2 This is a logic block diagram for classifying the current gaze action category of the detection target according to an embodiment of the invention. Figure 3 This is a logic block diagram of an embodiment of the invention for determining whether a pre-switched browsing page meets the visual stimulation standard. Figure 4 The present invention is a logic block diagram for determining whether to issue a management and control prompt in an embodiment of the present invention. The educational tablet system with management and control functions in an embodiment of the present invention includes:

[0057] A binocular detection module is provided on the educational tablet to obtain image data of the detection target;

[0058] An action analysis module, which is connected to the binocular detection module, is used to analyze the gaze action characteristics of the detection target based on the image data, calculate the visual concentration characterization parameter according to the gaze action characteristics, and classify the current gaze action category of the detection target;

[0059] A switching analysis module connected to the action analysis module, in response to the division result of the action analysis module, determines whether the pre-switching browsing page meets the visual stimulation standard according to the difference in visual image features between the current browsing page and the pre-switching browsing page, so as to optimize the pre-switching browsing page;

[0060] a feature analysis module, which is connected to the binocular detection module and the switching analysis module respectively, and is used to respond to the page switching moment, determine the visual stimulation time domain segment according to the page switching moment, and call the image data of the detection target in the visual stimulation time domain segment to analyze the pupil change characteristics;

[0061] A control module, which is connected to the feature analysis module, and is used to calculate visual impact parameters based on the pupil change features combined with the visual image features of the browsing page after switching, and determine whether to issue a control prompt;

[0062] The gaze action features include gaze vector deviation angle, facial gaze distance and gaze vector change frequency, and the visual image features include color quantity and color saturation mean.

[0063] Specifically, there is no limitation on the specific structure of the binocular detection module, which may be a binocular photography device. It is understandable that the binocular photography device can obtain the spatial coordinate data of each point of the detection target for subsequent analysis, which will not be elaborated here.

[0064] Specifically, there is no limitation on the specific structures of the action analysis module, switching analysis module, feature analysis module and management and control module, and they can all be composed of logical components or a combination of logical components, and the logical components include field programmable processors, computers or microprocessors in computers.

[0065] Specifically, the motion analysis module is used to analyze and detect the gaze motion features of the target based on the image data, including:

[0066] It is used to determine the facial reference plane of the monitoring target in the image data, and select any eye reference point in the facial reference plane to construct the normal vector of the facial reference plane as the gaze vector;

[0067] The angle between the gaze vector and the normal vector of the plane where the educational tablet is located is determined as the gaze vector offset angle. Preferably, the normal vector of the plane passes through the center of the screen of the educational tablet.

[0068] Determine the distance between the center of the facial reference plane and a predetermined reference point as the facial gaze distance;

[0069] The number of changes in the direction of the gaze vector within the reference time is used to determine the frequency of the gaze vector change;

[0070] Among them, the facial reference plane is a plane formed by two eye reference points and a forehead reference point, and the predetermined reference point is the center of the educational flat panel display. It can be understood that three points in space can form a unique and definite plane, which will not be repeated here.

[0071] It is understandable that the gaze action features are all determined in the same spatial coordinate system, which will not be described in detail.

[0072] The reference time is selected within [3s, 5s].

[0073] Specifically, an image processing model or algorithm capable of identifying gaze action features may be pre-trained and imported into a logic component to implement corresponding functions, which will not be elaborated herein.

[0074] Specifically, the action analysis module is used to calculate the visual focus characterization parameter based on the gaze action characteristics, including:

[0075] Determining the ratio of the gaze vector deviation angle to a preset standard gaze vector deviation angle standard threshold as the first visual focus influencing factor;

[0076] The ratio of the facial gaze distance to a preset facial gaze distance standard threshold is used to determine the second vision concentration influencing factor;

[0077] for determining the ratio of the gaze vector change frequency to a preset gaze vector change frequency standard threshold as the third visual focus influencing factor;

[0078] The first vision concentration influencing factor, the second vision concentration influencing factor and the third vision concentration influencing factor are weighted and summed to obtain a vision concentration characterization parameter.

[0079] Specifically, in implementation, the standard threshold of the standard gaze vector deviation angle is pre-set, wherein a number of image data corresponding to the detection target of the educational tablet at the time of page switching are pre-collected, the mean value of the gaze vector deviation angle is determined, and the mean value of the gaze vector deviation angle is set as the standard threshold of the standard gaze vector deviation angle.

[0080] Specifically, in implementation, the facial gaze distance standard threshold is selected within the interval [25cm, 30cm].

[0081] Specifically, in implementation, the standard threshold value of gaze vector change frequency is pre-set, wherein a number of image data corresponding to the detection target of the educational tablet within a reference time before and after the page switching moment are pre-collected, the average value of the gaze vector change frequency is determined, and the average value of the gaze vector change frequency is set as the standard threshold value of the gaze vector change frequency, and the reference time is half of the reference time.

[0082] Specifically, in implementation, when weighted summation is performed, the weight of the first vision focus influence factor is 0.45, the weight of the second vision focus influence factor is 0.2, and the weight of the third vision focus influence factor is 0.35.

[0083] The present invention calculates visual focus characterization parameters and classifies the current gaze action category of the detection target. In actual situations, when the user focuses on the screen, the user has data characterization in both the action dimension and the eye feature dimension. Therefore, the present invention extracts gaze action features, including a gaze vector offset angle, a facial gaze distance, and a gaze vector change frequency. The gaze vector offset angle is used to characterize whether the gaze direction is focused on the screen. The facial gaze distance can simply and reliably characterize whether a gaze action occurs. The gaze vector change frequency is used to characterize the degree of gaze concentration. Then, the visual focus characterization parameters are calculated to characterize the degree of gaze of the detection target on the screen, and data support is provided for classifying the gaze action category, so as to facilitate the subsequent timely calling of a switching analysis module, evaluate whether it meets the visual stimulation labeling, optimize the pre-switching page, and thus reduce the stimulation and influence on the vision during the use of the educational tablet, and improve the user experience.

[0084] Specifically, the action analysis module divides the current gaze action categories of the monitoring target into:

[0085] If the visual concentration characterization parameter is within a preset visual concentration characterization parameter interval, classifying the gaze action category as a strong gaze action category;

[0086] If the visual concentration characterization parameter is not within the preset visual concentration characterization parameter interval, the gaze action category is classified as a weak gaze action category.

[0087] When the target of the test is more focused on looking at the educational tablet, the visual acuity concentration characterization parameter fluctuates around 1. In implementation, the upper limit of the visual acuity concentration characterization parameter range is selected within the range [1.15, 1.3], and the lower limit is selected within the range [0.85, 0.95].

[0088] Specifically, the handover analysis module responds to the division result of the action analysis module including:

[0089] If the action analysis module classifies the gaze action category as a strong gaze action category, the action analysis module is started.

[0090] It is understandable that the activation of the motion analysis module means that the motion analysis module starts to execute the corresponding function, which will not be elaborated here.

[0091] Specifically, the switching analysis module is used to determine whether the pre-switching browsing page meets the visual stimulation standard and optimize the pre-switching browsing page, wherein:

[0092] for respectively determining a color quantity difference ratio and a color saturation mean value difference ratio between a browsing page and a pre-switched browsing page;

[0093] for determining the sum of the color quantity difference ratio and the color saturation difference ratio as the difference;

[0094] If the difference is greater than or equal to a preset difference threshold, the switching analysis module determines that the pre-switching browsing page does not meet the visual stimulation standard, and the pre-switching browsing page is optimized;

[0095] Among them, the optimization includes reducing the color saturation of each area of ​​the pre-switch browsing page.

[0096] Those skilled in the art may choose to reduce the color saturation ratio by themselves, and adaptably reduce the color saturation corresponding to each area of ​​the original browsing page, which will not be elaborated herein.

[0097] Specifically, the purpose of setting the difference threshold is to reflect the difference in visual image features between two browsing pages. In actual situations, when the color quantity difference ratio is greater than 0.3, it indicates that the difference between the browsing page images is large; when the color saturation difference ratio is greater than 0.25, it indicates that the difference between the browsing page images is large. Preferably, the difference threshold is selected in the interval [0.55, 0.75].

[0098] The difference ratio of two values ​​is the ratio of the absolute value of the difference between the two values ​​to the mean of the two values.

[0099] The segmentation analysis module of the present invention responds to the division result of the action analysis module. In actual situations, under relatively concentrated gaze, due to the adaptation mechanism of the human eye, it will relatively adapt to the visual image characteristics of the current browsing page, such as color saturation, etc. The use of educational tablets usually involves page switching. If there is a large difference between the pre-switching page and the current switching page, it will cause stimulation to the eye vision. Therefore, after dividing the gaze action category of the detection target, the present invention promptly analyzes the browsing page through the switching analysis module, and then intervenes in time to optimize the pre-switching browsing page, thereby reducing the visual stimulation and influence during the use of the educational tablet and improving the user experience.

[0100] Specifically, the feature analysis module determines a time domain segment corresponding to a predetermined time after a page switching moment as a visually stimulated time domain segment.

[0101] Preferably, the predetermined time is selected within the interval [0.25s, 0.5s].

[0102] Specifically, the feature analysis module is used to call the image data of the detection target in the visual stimulation time domain to analyze the pupil change characteristics, including:

[0103] Used to mark the pupil contour in each frame of image data and determine the maximum contour spacing of the pupil contour;

[0104] It is used to calculate the change amplitude of the maximum contour spacing in the visual stimulation time domain segment, and determine the change amplitude as the pupil change feature.

[0105] There is no limitation on the method of identifying the pupil contour, and the existing image segmentation algorithm can be used to identify the pupil contour. Of course, other methods can also be used to identify the pupil contour, which will not be described in detail.

[0106] Specifically, the control module is used to calculate the visual impact parameters.

[0107] The ratio of the color quantity to the preset color quantity standard threshold is used to calculate the first visual impact factor;

[0108] The ratio of the color saturation mean value to the preset color saturation standard threshold value is used to calculate the second visual impact factor;

[0109] Used to determine the sum of the first visual impact factor and the second visual impact factor as a visual impact parameter.

[0110] Specifically, the color quantity threshold and the color saturation threshold are pre-set, wherein a number of browsing pages are pre-acquired as samples, the color quantity and color saturation average of the browsing pages are recorded, the first average of the color quantity and the second average of the color saturation average of each browsing page are calculated, and the color quantity threshold is set to 1.3 times the first average, and the color saturation threshold is set to 1.15 times the second average.

[0111] It is understandable that for the human eye, highly saturated colors may cause visual discomfort and visual fatigue when looking at them. Similarly, an increase in the number of colors, especially highly saturated colors, can easily cause eye fatigue. Due to the adaptive mechanism of the human eye, more adjustments are needed to adapt to these bright colors, which in turn causes eye fatigue.

[0112] Specifically, the control module determines whether to issue a control prompt including:

[0113] If the visual impact parameter is greater than a preset visual impact parameter threshold, it is determined to issue a control prompt.

[0114] In implementation, the visual impact parameter threshold is selected within the interval [2.15, 2.3].

[0115] There is no specific limitation on the control prompts. For example, you can prompt to increase the gaze distance or reduce the gaze time.

[0116] The feature analysis module of the present invention calls the image data in the visual stimulation time domain to analyze the pupil change characteristics. In actual situations, the pupil of the human eye will change after being stimulated. Therefore, the pupil change characteristics in the visual stimulation time domain are monitored, and the visual image characteristics of the browsing page after switching are analyzed. Consider whether there is a high eye irritation in the browsing page after switching, and then issue a control prompt in time to reduce the visual stimulation and influence during the use of the educational tablet, thereby improving the user experience.

[0117] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

Claims

1. An educational tablet system with management and control functions, characterized in that: include: A binocular detection module is provided on the educational tablet to obtain image data of the detection target; An action analysis module, which is connected to the binocular detection module, is used to analyze the gaze action characteristics of the detection target based on the image data, calculate the visual concentration characterization parameter according to the gaze action characteristics, and classify the current gaze action category of the detection target; A switching analysis module connected to the action analysis module, in response to the division result of the action analysis module, determines whether the pre-switching browsing page meets the visual stimulation standard according to the difference in visual image features between the current browsing page and the pre-switching browsing page, so as to optimize the pre-switching browsing page; a feature analysis module, which is connected to the binocular detection module and the switching analysis module respectively, and is used to respond to the page switching moment, determine the visual stimulation time domain segment according to the page switching moment, and call the image data of the detection target in the visual stimulation time domain segment to analyze the pupil change characteristics; A control module, which is connected to the feature analysis module, and is used to calculate visual impact parameters based on the pupil change features combined with the visual image features of the browsing page after switching, and determine whether to issue a control prompt; The gaze action features include gaze vector deviation angle, facial gaze distance and gaze vector change frequency, and the visual image features include color quantity and color saturation mean.

2. The educational tablet system with management and control function according to claim 1, characterized in that: The motion analysis module is used to analyze and detect the gaze motion features of the target based on the image data, including: It is used to determine the facial reference plane of the monitoring target in the image data, and select any eye reference point in the facial reference plane to construct the normal vector of the facial reference plane as the gaze vector; The angle between the gaze vector and the normal vector of the plane where the educational tablet is located is determined as the gaze vector offset angle; Determine the distance between the center of the facial reference plane and a predetermined reference point as the facial gaze distance; The number of changes in the direction of the gaze vector within the reference time is used to determine the frequency of the gaze vector change; The facial reference plane is a plane formed by two eye reference points and a forehead reference point, and the predetermined reference point is the center of the educational flat panel display screen.

3. The educational tablet system with management and control function according to claim 2, characterized in that: The action analysis module is used to calculate the visual focus characterization parameter based on the gaze action characteristics, including: Determining the ratio of the gaze vector deviation angle to a preset standard gaze vector deviation angle standard threshold as the first visual focus influencing factor; The ratio of the facial gaze distance to a preset facial gaze distance standard threshold is used to determine the second vision concentration influencing factor; for determining the ratio of the gaze vector change frequency to a preset gaze vector change frequency standard threshold as the third visual focus influencing factor; The first vision concentration influencing factor, the second vision concentration influencing factor and the third vision concentration influencing factor are weighted and summed to obtain a vision concentration characterization parameter.

4. The educational tablet system with management and control function according to claim 3, characterized in that: The action analysis module divides the current gaze action categories of the monitoring target into: If the visual concentration characterization parameter is within a preset visual concentration characterization parameter interval, classifying the gaze action category as a strong gaze action category; If the visual concentration characterization parameter is not within the preset visual concentration characterization parameter interval, the gaze action category is classified as a weak gaze action category.

5. The educational tablet system with management and control function according to claim 1, characterized in that: The handover analysis module responds to the division result of the action analysis module including: If the action analysis module classifies the gaze action category as a strong gaze action category, the action analysis module is started.

6. The educational tablet system with management and control function according to claim 1, characterized in that: The switching analysis module is used to determine whether the pre-switching browsing page meets the visual stimulation standard and optimize the pre-switching browsing page, wherein: for respectively determining a color quantity difference ratio and a color saturation mean value difference ratio between a browsing page and a pre-switched browsing page; for determining the sum of the color quantity difference ratio and the color saturation difference ratio as the difference; If the difference is greater than or equal to a preset difference threshold, the switching analysis module determines that the pre-switching browsing page does not meet the visual stimulation standard, and the pre-switching browsing page is optimized; Among them, the optimization includes reducing the color saturation of each area of ​​the pre-switch browsing page.

7. The educational tablet system with management and control function according to claim 1, characterized in that: The feature analysis module determines a time domain segment corresponding to a predetermined time after a page switching moment as a visually stimulated time domain segment.

8. The educational tablet system with management and control function according to claim 1, characterized in that: The feature analysis module is used to call the image data of the detected target in the visual stimulation time domain to analyze the pupil change characteristics, including: Used to mark the pupil contour in each frame of image data and determine the maximum contour spacing of the pupil contour; It is used to calculate the change amplitude of the maximum contour spacing in the visual stimulation time domain segment, and determine the change amplitude as the pupil change feature.

9. The educational tablet system with management and control function according to claim 1, characterized in that: The control module is used to calculate the visual impact parameters. The ratio of the color quantity to the preset color quantity standard threshold is used to calculate the first visual impact factor; The ratio of the color saturation mean value to the preset color saturation standard threshold value is used to calculate the second visual impact factor; Used to determine the sum of the first visual impact factor and the second visual impact factor as a visual impact parameter.

10. The educational tablet system with management and control function according to claim 1, characterized in that: The control module determines whether to issue a control prompt including: If the visual impact parameter is greater than a preset visual impact parameter threshold, it is determined to issue a control prompt.

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