Meteorological science popularization display method and system based on immersive technology

Abstract

The invention discloses a meteorological science popularization display method and system based on an immersive technology, and relates to the technical field of image processing, and the method comprises the steps: obtaining screen image data and human eye attention data, carrying out the preprocessing of the screen image data and the human eye attention data, carrying out the evaluation of the preprocessed screen image data and human eye attention data, and obtaining a meteorological science popularization display result. Obtaining an evaluation value of the external light entering equipment, and judging the external light permeation equipment according to a result of the evaluation value of the external light entering equipment. The screen image data is acquired and the image color difference degree, the brightness difference degree and the contrast difference degree are evaluated to judge whether external light permeates into the head-mounted equipment to influence the immersion experience of a user, and the immersion feeling and the visual comfort of the user are enhanced by reducing ambient light interference and adjusting a display mode, so that the user experience is improved, and the user experience is improved. Meanwhile, a vivid three-dimensional virtual environment is provided, and the attraction and effect of meteorological science popularization education are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of image processing, and in particular to a meteorological science popularization display method and system based on immersive technology. Background Art

[0002] The application of immersive technology in meteorological science popularization displays refers to the use of virtual reality (VR) and other technical means to create a three-dimensional virtual environment that simulates real meteorological phenomena, allowing users to experience and learn meteorological knowledge "immersively" through head-mounted displays or other interactive devices. This display method can provide an intuitive visual experience of meteorological changes, such as simulating hurricanes, lightning, rain and snow, and at the same time, combined with interactive elements, allowing users to have a deeper understanding of the working principles of the meteorological system and the scientific principles of weather changes, thereby increasing the appeal and effectiveness of science popularization education.

[0003] Immersive technology can significantly increase people's interest in meteorology by providing realistic three-dimensional virtual environments and multi-sensory interactive experiences. It allows the public to intuitively experience meteorological phenomena in a safe and controllable simulated environment. This novel and interactive science popularization method promotes a deeper understanding and interest in meteorological science.

[0004] For example, the invention patent with publication number CN205987196U discloses a naked-eye 3D virtual reality display system, which includes using a VR sensor unit to collect gamers' motion information, issuing trigger or control instructions to a three-dimensional rendering unit, triggering or controlling the three-dimensional virtual scene of the three-dimensional rendering unit, obtaining a rendered image, and sending it to a VR display unit, so that gamers can have an immersive virtual reality experience; at the same time, an actual stereo camera array is used, and the green screen matting technology is combined to place the gamers themselves in a digital virtual scene, and finally the gamers and the virtual scene are presented in a naked-eye 3D display, so that bystanders can observe the scene that the gamers are experiencing from a third perspective without the aid of any auxiliary equipment; bystanders can also manually adjust the viewing position and angle of the third perspective, so as to watch what is happening in the virtual scene according to their own interests, and can also observe and analyze the entire virtual scene in all directions.

[0005] For example, the invention patent with publication number CN118394218A discloses an immersive virtual reality display system based on big data technology, which includes a full-time joint analysis of the gesture action images of the user object at multiple predetermined time points within a predetermined detection time period through an intelligent algorithm to understand the full-time interactive behavior pattern of the user object, rather than just the gesture information of a single moment, and use this full-time interactive behavior pattern information to judge the real interactive intention of the user object, and then control the behavior of the digital human in the immersive virtual reality display system based on big data technology, so as to map the interactive intention of the user object to the behavior of the digital human, and improve the interactivity and realism of the system.

[0006] When ambient light penetrates into the gap between the head-mounted virtual reality device and the user's face, it will weaken the clarity and three-dimensional depth of the image, affecting the user's feeling of immersion in the virtual environment. Wearing the head-mounted virtual reality device for a long time will also cause discomfort to the user's eyes, which in turn affects the user's involvement in the virtual reality scene and satisfaction with the meteorological science display. Summary of the invention

[0007] Technical issues solved

[0008] In view of the shortcomings of the prior art, the present invention provides a meteorological science display method and system based on immersive technology, which solves the problem that the temperature difference between the initial fire source and the surrounding environment is not obvious, making it impossible for drones to accurately detect the fire point, delaying the timely discovery of the fire.

[0009] Technical Solution

[0010] To achieve the above objectives, the present invention is implemented through the following technical solutions: a meteorological science popularization display method and system based on immersive technology, comprising the following specific steps: step one: obtaining screen image data and human eye attention data, preprocessing the screen image data and human eye attention data, evaluating the preprocessed screen image data and human eye attention data, and obtaining an external light entering the device evaluation value; step two: judging the external light penetration device according to the result of obtaining the external light entering the device evaluation value; step three: if it is judged that there is an external light penetration device, tighten the immersive device to fit the face, and return to step one to continue to obtain screen image data and human eye attention data; if it is judged that there is no external light penetration device, execute step four; step four: obtaining human eye status data, preprocessing the human eye status data, evaluating the preprocessed human eye status data, and obtaining a human eye discomfort evaluation value; step five: judging human eye discomfort according to the result of obtaining the human eye discomfort evaluation value; step six: if it is judged that there is human eye discomfort, adjust the screen, and return to step four to continue to obtain human eye status data until it is judged that there is no eye discomfort; if it is judged that there is no eye discomfort, perform meteorological science popularization display.

[0011] Furthermore, in step 1, a detection time period is set; the screen image data and the human eye attention data are filtered and denoised; the screen image data includes pixel points, BGR color space, Lab values ​​of pixel points, brightness values ​​of pixel points and standard deviations of pixel points; the human eye attention data includes eyeball contour positions and gaze point positions; image color difference, image brightness difference and image contrast difference are obtained through comprehensive analysis of the screen image data; the image color difference, image brightness difference and image contrast difference are normalized; and the image color difference, image brightness difference and image contrast difference after normalization are obtained. The screen image abnormality coefficient is obtained by evaluating the image contrast difference; the degree of eye saccade, the fixation time on the fixation point position, and the number of changes in the eye fixation point position during the detection period are obtained by comprehensive analysis of the human eye attention data; the degree of eye saccade, the fixation time on the fixation point position, and the number of changes in the eye fixation point position during the detection period are normalized; the human eye inconcentration coefficient is obtained based on the normalized degree of eye saccade, the fixation time on the fixation point position, and the number of changes in the eye fixation point position during the detection period; the method for obtaining the external light entering the device evaluation value based on the evaluation of the screen image abnormality coefficient and the human eye inconcentration coefficient is as follows: Among them, WG represents the evaluation value of external light entering the device, PY represents the screen image abnormality coefficient, and RB represents the human eye inattention coefficient.

[0012] Furthermore, the specific steps of obtaining the image color difference, image brightness difference and image contrast difference through comprehensive analysis of screen image data are as follows: using an edge detection algorithm to obtain the edge of the pixel and segment it, divide the local area, and calculate the area of ​​the local area; using a color difference detection algorithm, converting the image from the BGR color space to the Lab color space; obtaining the average Lab value of each local area through the Lab value of each local area pixel, and performing a difference calculation between the Lab value of the pixel in each local area and the average Lab value of the local area; summing the absolute value results of the difference calculation to obtain the color difference of the local area of ​​the image, and summing the color difference of each local area of ​​the image to obtain the image color difference; converting the image from the Lab color space to a gray image; summing the brightness values ​​of the pixels in the local area; The result of summing up the brightness values ​​of the pixels in the local area is divided by the area of ​​the local area to obtain the average brightness value of the local area; the average brightness values ​​of each local area are summed and averaged to obtain the average brightness value of the image; the average brightness value of each local area is calculated by difference with the average brightness value of the image to obtain the brightness difference value; the absolute value of the brightness difference values ​​is summed to obtain the image brightness difference; the contrast of the pixel is obtained by the ratio of the standard deviation of the pixel points in each local area to the average brightness value; the contrast of the pixel points in each local area is summed and averaged to obtain the average contrast of the local area; the average contrast of each local area is summed and averaged to obtain the image average contrast; the average contrast of each local area is calculated by difference with the average contrast of the image; the absolute value results of the difference calculation are summed to obtain the image contrast difference.

[0013] Furthermore, the specific steps of obtaining the degree of eye saccade, the fixation time on the fixation point position and the number of changes in the eye fixation point position within the detection time period through comprehensive analysis of human eye attention data are as follows: in the initial stage of the detection time period, the eye contour position is obtained by an edge detection algorithm; within the detection time period, the distance moved by the eye contour position, the number of times the eye contour position moves and the direction of the eye contour position movement are obtained by an edge motion tracking algorithm; the eye saccade amplitude is obtained by calculating the absolute value of the difference in the distance of the eye contour position movement; the eye saccade frequency is obtained by the ratio of the number of times the eye contour position moves to the detection time period; the eye saccade angle is obtained by the absolute value of the angular difference in the direction of the eye contour position movement; the eye saccade degree is obtained according to the product of the eye saccade amplitude, the eye saccade frequency and the eye saccade angle; and the eye saccade angle is tracked by the edge motion tracking algorithm. The movement of the eyeball contour position, when the eyeball contour position is stationary with respect to the fixation point position, the timing starts, and when the eyeball contour position moves, the timing stops, and the fixation time of a single fixation point position is obtained; within the detection time period, the sum of the fixation time of a single fixation point position is calculated and then the average is obtained to obtain the fixation time of the fixation point position; S1: a fixation threshold is set according to the fixation time of the fixation point position, and within the detection time period, when the fixation time of the eyeball on the fixation point position is greater than or equal to the fixation threshold, it is regarded as the eyeball fixating on the fixation point position; S2: a saccade threshold is set according to the degree of saccades, and within the detection time period, when the eyeball contour position moves each time and the next position is inconsistent with the previous position, it is regarded as the eyeball looking at other fixation point positions; according to S1 and S2, the number of changes in the eyeball fixation point position within the detection time period is obtained.

[0014] Furthermore, in step two, an external light penetration device threshold is set and compared with the external light entry device evaluation value; when the external light entry device evaluation value is greater than or equal to the external light penetration device threshold, it is judged that there is an external light penetration device; when the external light entry device evaluation value is less than the external light penetration device threshold, it is judged that there is no external light penetration device.

[0015] Further, in step 4, filtering and denoising are performed on the human eye state data; the human eye state data includes a human eye image, a number of frames of the human eye image, an eyelid contour, an area of ​​the eyeball, and an area of ​​the eyelid contour; the degree of pupil constriction and the degree of eye closure are obtained by comprehensive analysis of the human eye state data after filtering and denoising; the degree of pupil constriction and the degree of eye closure are normalized; the human eye state abnormality coefficient is obtained according to the normalized degree of pupil constriction and the degree of eye closure; the method for obtaining the human eye discomfort assessment value according to the human eye state abnormality coefficient and the human eye inconcentration coefficient is as follows: Among them, RP represents the human eye discomfort assessment value, RB represents the human eye unfocus coefficient, and ZY represents the human eye state abnormality coefficient.

[0016] Furthermore, the specific steps of comprehensively analyzing the human eye state data after filtering and denoising to obtain the pupil constriction degree and the eye closure degree are as follows: using an edge detection algorithm and an edge motion tracking algorithm to calculate the human eye image to obtain the pupil area of ​​each frame of the human eye image; summing and averaging the pupil area of ​​each frame of the human eye image according to the number of human eye image frames to obtain the average pupil area within the detection time period; performing difference calculation between the pupil area of ​​each frame of the human eye image and the average pupil area within the detection time period; using statistical principles, setting a pupil area threshold according to the average pupil area, and when the result of the difference calculation is less than the pupil area threshold, screening the pupil area of ​​each frame of the human eye image; selecting all pupil areas of each frame of the human eye image that meet the conditions, and summing the absolute values ​​of the differences between them and the average pupil area to obtain the pupil constriction degree; using the edge detection algorithm and the edge motion tracking algorithm to obtain the movement trajectory of the eyelid contour within the detection time period; When the area of ​​the eyelid contour increases until it stops and the area of ​​the eyeball decreases until it stops, a closed eye threshold is set; when the area of ​​the eyelid contour decreases until it stops and the area of ​​the eyeball increases until it stops, an open eye threshold is set; when the area of ​​the eyelid contour increases until it stops and the area of ​​the eyeball decreases until it stops, the timing starts, and the timing is stopped when the area of ​​the eyelid contour decreases and the area of ​​the eyeball increases, thereby obtaining the closed eye duration; the eye closing durations of multiple times within the detection time period are summed and then averaged to obtain the single closed eye duration; using statistical principles, the number of human eye images that meet the closed eye threshold within the detection time period are counted to obtain the number of closed eyes within the detection time period; when the area of ​​the eyelid contour and the area of ​​the eyeball are between the closed eye threshold and the open eye threshold, it indicates squinting; the area of ​​the eyelid contour of each frame of the human eye image when squinting is summed and then averaged to obtain the squinting range; the closed eye degree is obtained according to the product of the single closed eye duration, the number of closed eyes within the detection time period and the squinting range.

[0017] Furthermore, in step five, a human eye discomfort threshold is set and compared with the human eye discomfort evaluation value; when the human eye discomfort evaluation value is greater than or equal to the human eye discomfort threshold, it is judged that human eye discomfort exists; when the human eye discomfort evaluation value is less than the human eye discomfort threshold, it is judged that no human eye discomfort exists.

[0018] Furthermore, the specific steps of adjusting the screen are: reducing the screen brightness and contrast, and improving the clarity of the screen image until it is determined that no one's eyes are uncomfortable.

[0019] Furthermore, there are a data acquisition module, a data analysis module, a data execution module and an immersive module; the data acquisition module is used to acquire screen image data, human eye attention data and human eye status data and pre-process them, and send the pre-processed data to the data analysis module; the data analysis module is used to receive the data sent by the data acquisition module, analyze and judge the discomfort of the external light penetration device and the human eye, and send the judgment result to the data execution module; the data execution module is used to receive the judgment result of the data analysis module, and execute the judgment result of the external light penetration device and the discomfort of the human eye; the immersive module includes an immersive device and a screen, and the data execution module adjusts the immersive device and the screen according to the judgment result of the external light penetration device and the discomfort of the human eye.

[0020] Beneficial Effects

[0021] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0022] 1. By acquiring screen image data and evaluating the image color difference, brightness difference, and contrast difference, it is used to determine whether external light has penetrated into the head-mounted device and affected the user's immersive experience.

[0023] 2. By obtaining human eye attention data and evaluating the degree of eye saccades, the fixation time on the fixation point position, and the number of changes in the eye fixation point position, it is used to determine whether the user is distracted by external light.

[0024] 3. By obtaining human eye status data and evaluating the degree of pupil constriction and eye closure, it is used to determine whether the user feels eye discomfort due to long-term use of the device.

[0025] 4. By reducing ambient light interference and adjusting the display mode, the user's sense of immersion and visual comfort can be enhanced, while providing a realistic three-dimensional virtual environment to enhance the appeal and effectiveness of meteorological science education.

[0026] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 The present invention is a flow chart of a meteorological science popularization display method based on immersive technology.

[0028] Figure 2 For the present invention: image difference and abnormal coefficient line graph.

[0029] Figure 3 This invention: a structural diagram of a meteorological science display system based on immersive technology. DETAILED DESCRIPTION

[0030] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] It should be noted that, in this article, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0032] like Figure 1 As shown, an embodiment of the present invention provides a meteorological science popularization display method based on immersive technology, which includes the following specific steps:

[0033] Step 1: An image capture device is set in the immersive device to obtain screen image data and human eye attention data, pre-process the screen image data and human eye attention data, evaluate the pre-processed screen image data and human eye attention data, and obtain an evaluation value of external light entering the device.

[0034] Set the detection time period;

[0035] Filtering and denoising the screen image data and human eye attention data helps to reduce the amount of data in subsequent processing, reduce computational complexity and resource consumption;

[0036] By acquiring screen image data and evaluating the image color difference, brightness difference, and contrast difference, it is used to determine whether external light has penetrated into the immersive device and affected the user's immersive experience;

[0037] By obtaining human eye attention data and evaluating the degree of eye saccades, the fixation time and the number of changes in the eye fixation point position, it is used to determine whether the user is distracted by external light;

[0038] Screen image data includes pixels, BGR color space, Lab values ​​of pixels, brightness values ​​of pixels, and standard deviations of pixels;

[0039] Human eye attention data includes the position of the eyeball contour and the position of the fixation point;

[0040] The image color difference, image brightness difference and image contrast difference are obtained by comprehensive analysis of screen image data;

[0041] Normalizing the image color difference, image brightness difference, and image contrast difference helps improve the efficiency of calculation;

[0042] The method for obtaining the screen image abnormality coefficient based on the evaluation of the normalized image color difference, image brightness difference and image contrast difference is as follows:

[0043]

[0044] Among them, PY represents the screen image abnormality coefficient, SC represents the image color difference, external light penetration equipment interferes with the image color, LD represents the image brightness difference, external light penetration equipment interferes with the image brightness, DB represents the image contrast difference, external light penetration equipment interferes with the image contrast.

[0045] Table 1 Relationship between image color difference, image brightness difference and image contrast difference and approximate value of screen image abnormality coefficient

[0046]

[0047] As shown in Table 1, when the image color difference is 26, the image brightness difference is 82, and the image contrast difference is 12, the approximate value of the screen image abnormality coefficient is 14.63; when the image color difference is 33, the image brightness difference is 127, and the image contrast difference is 22, the approximate value of the screen image abnormality coefficient is 22.69; when the image color difference is 41, the image brightness difference is 198, and the image contrast difference is 43, the approximate value of the screen image abnormality coefficient is 34.98; as the image color difference, image brightness difference, and image contrast difference increase, the approximate value of the screen image abnormality coefficient also increases, indicating that these image differences are important factors affecting the screen image abnormality coefficient. In order to reduce the screen image abnormality coefficient, external light can be prevented from penetrating into the device.

[0048] like Figure 2 As shown, using an edge detection algorithm, such as the Sobel algorithm, the edge of the pixel is detected and segmented, the local area is divided, and the area of ​​the local area is calculated;

[0049] The Sobel algorithm uses two 3x3 convolution kernels to filter the image in the x and y directions respectively, and then combines the results in these two directions to determine the edge strength and direction.

[0050] The specific steps to obtain the image color difference are:

[0051] Using a color difference detection algorithm, such as a CIE color difference detection algorithm, to convert the image from the BGR color space to the Lab color space;

[0052] The average Lab value of each local area is obtained by the Lab value of each local area pixel, and the difference between the Lab value of each local area pixel and the average Lab value of the local area is calculated;

[0053] The absolute value results of the difference calculation are summed to obtain the color difference of the local area of ​​the image, and the color difference of each local area of ​​the image is summed to obtain the image color difference;

[0054] The CIE color difference detection algorithm is a standardized method for quantifying and evaluating the visual difference between two colors. It determines the perceived color difference between colors by calculating the differences in the three components of color in the Lab color space: L* (brightness), a* (red-green axis), and b* (yellow-blue axis).

[0055] The specific steps to obtain the image brightness difference are:

[0056] Converting the image from Lab color space to gray image helps improve computational efficiency;

[0057] Sum the brightness values ​​of the pixels in the local area, and the brightness value is between 0 (black) and 255 (white);

[0058] The sum of the brightness values ​​of the pixels in the local area is divided by the area of ​​the local area to obtain the average brightness value of the local area;

[0059] The average brightness value of each local area is summed and averaged to obtain the average brightness value of the image;

[0060] The average brightness value of each local area is calculated by subtracting the average brightness value of the image to obtain the brightness difference value;

[0061] The absolute value of the brightness difference is summed to obtain the image brightness difference.

[0062] The specific steps to obtain the image contrast difference are:

[0063] The contrast of the pixel is obtained by the ratio of the standard deviation of each local area pixel to the average brightness value. The larger the standard deviation, the greater the change in image brightness and the higher the contrast.

[0064] The contrast of each pixel in the local area is summed and averaged to obtain the average contrast of the local area;

[0065] The average contrast of each local area is summed and averaged to obtain the average contrast of the image;

[0066] Calculate the difference between the average contrast of each local area and the average contrast of the image;

[0067] The absolute value results of the difference calculation are summed to obtain the image contrast difference.

[0068] Through comprehensive analysis of human eye attention data, the degree of eye saccade, the fixation time on the fixation point position, and the number of changes in the eye fixation point position during the detection period are obtained;

[0069] Normalizing the degree of saccades, the fixation time on the fixation point, and the number of changes in the fixation point during the detection period helps to improve the efficiency of calculation;

[0070] The method for obtaining the human eye inconcentration coefficient according to the normalized eye saccade degree, the fixation time on the fixation point position, and the number of changes in the eye fixation point position during the detection period is as follows:

[0071]

[0072] Among them, RB represents the eye inconcentration coefficient, YT represents the degree of eye saccade, ZS represents the fixation time on the fixation point position, and ZC represents the number of changes in the eye fixation point position within the detection time period.

[0073] The specific steps and methods for obtaining the degree of eye saccade are as follows:

[0074] In the initial stage of the detection period, the position of the eyeball contour is detected by edge detection algorithm;

[0075] During the detection period, the distance moved by the eyeball contour position, the number of times the eyeball contour position moves, and the direction of the eyeball contour position movement are obtained through the edge motion tracking algorithm;

[0076] The saccade amplitude is obtained by calculating the absolute value of the distance difference of the eyeball contour position movement;

[0077] The saccade frequency is obtained by the ratio of the number of eye contour position movements to the detection time period;

[0078] The saccade angle is obtained by the absolute value of the angle difference in the direction of the eyeball contour position movement;

[0079] The degree of saccade is obtained by multiplying the saccade amplitude, saccade frequency and saccade angle.

[0080] Edge motion tracking algorithms, such as edge walking algorithms, start from a point on a detected edge, move along edge pixels, and track the entire edge path point by point according to a predefined search direction or edge strength change. When the edge path reaches the end or encounters a point where the edge strength no longer meets the conditions, the algorithm stops, thereby achieving complete tracking of continuous edges in the image.

[0081] The specific steps to obtain the fixation time of the fixation point position are:

[0082] The movement of the eyeball contour position is tracked by an edge motion tracking algorithm. When the eyeball contour position is stationary relative to the fixation point position, timing starts, and when the eyeball contour position moves, timing stops, thereby obtaining a single fixation time relative to the fixation point position.

[0083] During the detection period, the sum of the individual fixation times at the fixation point positions is calculated and then averaged to obtain the fixation time at the fixation point positions.

[0084] The specific steps for obtaining the number of changes in the eye gaze point position during the detection period are:

[0085] S1: Set the fixation threshold according to the fixation time of the fixation point. During the detection period, when the fixation time of the eyeball on the fixation point is greater than or equal to the fixation threshold, it is regarded as the eyeball fixating on the fixation point.

[0086] S2: Set the eye saccade threshold according to the degree of eye saccade. During the detection period, when the position of the eyeball contour moves each time and the next position is inconsistent with the previous position, it is regarded as the eyeball looking at other fixation points.

[0087] The number of changes in the eye gaze point position during the detection time period is obtained based on S1 and S2.

[0088] The method for obtaining the external light entering the device evaluation value based on the evaluation of the screen image abnormality coefficient and the human eye inconcentration coefficient is as follows:

[0089]

[0090] Among them, WG represents the evaluation value of external light entering the device, PY represents the screen image abnormality coefficient, external light entering the device causes the image to be unclear, and RB represents the human eye inattention coefficient, external light entering the device will interfere with people's attention.

[0091] Step 2: Make an external light penetration device judgment based on the result of the external light entry device evaluation value.

[0092] Set the external light penetration device threshold and compare it with the external light entry device assessment value;

[0093] The external light penetration device threshold obtains the external light penetration device experimental data through the screen image data and the human eye attention data;

[0094] The external light penetration device experimental data is stored in the external light penetration device database and called.

[0095] When the external light entering the device evaluation value is greater than or equal to the external light penetrating device threshold, it is determined that there is an external light penetrating device;

[0096] When the external light entering the device evaluation value is less than the external light penetrating device threshold, it is determined that there is no external light penetrating device.

[0097] Step 3: If it is determined that there is an external light penetration device, adjust the immersive device to fit the face. When the immersive device is in contact with the face on all sides, stop adjusting to avoid gaps that allow external light to penetrate into the device, and return to step 1 to continue obtaining screen image data and human eye attention data; if it is determined that there is no external light penetration device, execute step 4.

[0098] Step 4: obtaining human eye status data through an image capturing device, preprocessing the human eye status data, and evaluating the preprocessed human eye status data to obtain a human eye discomfort evaluation value.

[0099] Filtering and denoising the human eye status data helps to reduce the amount of data in subsequent processing, reduce computational complexity and resource consumption;

[0100] By obtaining human eye status data and evaluating the degree of pupil constriction and eye closure, it is used to determine whether the user feels eye discomfort due to long-term use of the device.

[0101] The human eye status data includes the pupil area, the eyeball area, and the eyelid contour area;

[0102] The degree of pupil constriction and eye closure are obtained by comprehensive analysis of the human eye status data after filtering and denoising;

[0103] Normalizing the pupil constriction and eye closure degree helps improve the efficiency of calculation;

[0104] The method for obtaining the abnormal coefficient of human eye state according to the normalized pupil constriction and eye closure degree is as follows:

[0105]

[0106] Among them, ZY represents the abnormal coefficient of human eye status, TS represents the degree of pupil constriction. Light stimulation will cause pupil constriction. BC represents the degree of eye closure. If the eyes are uncomfortable, the eyes will be closed and the use of the eyes will be reduced.

[0107] The specific steps to obtain the pupil constriction degree are:

[0108] The pupil area of ​​each frame of the human eye image is obtained by calculating the human eye image using the edge detection algorithm and the edge motion tracking algorithm;

[0109] According to the number of human eye image frames, the pupil area of ​​each frame of the human eye image is summed and then averaged to obtain the average pupil area in the detection time period;

[0110] The pupil area of ​​each frame of the human eye image is summed and averaged to obtain the average pupil area during the detection time period;

[0111] Calculate the difference between the pupil area of ​​each frame of human eye image and the average pupil area during the detection time period;

[0112] Using statistical principles, the pupil area threshold is set according to the average pupil area. When the result of the difference calculation is less than the pupil area threshold, the pupil area of ​​each frame of the human eye image is screened;

[0113] The pupil areas of all qualified human eye images in each frame are selected, and the absolute values ​​of the differences between them and the average pupil area are summed to obtain the pupil reduction degree.

[0114] The specific steps to obtain the degree of eye closure are:

[0115] During the detection period, the movement trajectory of the eyelid contour is obtained using the edge detection algorithm and the edge motion tracking algorithm;

[0116] If the area of ​​the eyelid contour increases to a stop and the area of ​​the eyeball decreases to a stop within 0.3 seconds to 1 second, the eye-closing threshold is set; if the area of ​​the eyelid contour decreases to a stop and the area of ​​the eyeball increases to a stop, the eye-opening threshold is set. 0.3 seconds to 1 second is the normal blinking cycle of humans;

[0117] When the area of ​​the eyelid contour increases to a stop and the area of ​​the eyeball decreases to a stop within 0.3 seconds to 1 second, start timing, and stop timing when the area of ​​the eyelid contour decreases and the area of ​​the eyeball increases, and get the duration of eye closure;

[0118] The duration of multiple eye closures within the detection period is summed and then averaged to obtain the duration of a single eye closure;

[0119] Using statistical principles, the number of human eye images that meet the eye closing threshold within the detection period is counted to obtain the number of eye closing times within the detection period;

[0120] When the area of ​​the eyelid contour and the area of ​​the eyeball are between the closed-eye threshold and the open-eye threshold, it indicates squinting;

[0121] The area of ​​the eyelid contour of each frame of the human eye image when squinting is summed and then averaged to obtain the squinting range;

[0122] The degree of eye closure is obtained by multiplying the duration of a single eye closure, the number of eye closures during the detection period, and the squinting range;

[0123] The method for obtaining the human eye discomfort assessment value based on the human eye state abnormality coefficient and the human eye inconcentration coefficient is as follows:

[0124]

[0125] Among them, RP represents the human eye discomfort assessment value, RB represents the human eye unfocus coefficient, and ZY represents the human eye state abnormality coefficient.

[0126] Step 5: Make a judgment on the discomfort of the human eye based on the result of the evaluation value of the discomfort of the human eye.

[0127] Set the human eye discomfort threshold and compare it with the human eye discomfort assessment value;

[0128] The human eye discomfort threshold obtains the human eye discomfort experimental data through the human eye status data;

[0129] The human eye discomfort experiment data is stored in the human eye discomfort database and called.

[0130] When the human eye discomfort assessment value is greater than or equal to the human eye discomfort threshold, it is judged that there is human eye discomfort;

[0131] When the human eye discomfort evaluation value is less than the human eye discomfort threshold, it is determined that there is no human eye discomfort.

[0132] Step 6: If it is determined that someone's eyes are uncomfortable, adjust the screen and lower it until no one's eyes are uncomfortable, reduce the pressure on the eyes, and return to step 4 to continue to obtain human eye status data; if it is determined that no one's eyes are uncomfortable, conduct a meteorological science demonstration.

[0133] like Figure 3 As shown: A meteorological science popularization display system based on immersive technology, including: a data acquisition module, a data analysis module, a data execution module and an immersive module;

[0134] The data acquisition module is used to acquire screen image data, human eye attention data and human eye status data and pre-process them, and send the pre-processed data to the data analysis module;

[0135] The data analysis module is used to receive the data sent by the data acquisition module, analyze and judge the external light penetration device and the discomfort of the human eye, and send the judgment result to the data execution module;

[0136] The data execution module is used to receive the judgment result of the data analysis module and execute the judgment result of the external light penetration device and the discomfort of the human eye;

[0137] The immersive module includes an immersive device and a screen. The data execution module adjusts the immersive device and the screen according to the judgment result of the external light penetration device and the discomfort of the human eye.

[0138] By reducing ambient light interference and adjusting the display mode, the user's immersion and visual comfort are enhanced, while providing a realistic three-dimensional virtual environment to improve the appeal and effectiveness of meteorological science education.

[0139] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A meteorological science popularization display method based on immersive technology, characterized by: The specific steps include: Step 1: obtaining screen image data and human eye attention data, preprocessing the screen image data and human eye attention data, evaluating the preprocessed screen image data and human eye attention data, and obtaining an evaluation value of external light entering the device; Step 2: judging the external light penetration device according to the result of obtaining the external light penetration device evaluation value; Step 3: If it is determined that there is external light penetration, the immersive device is adjusted to fit the face, and the process returns to step 1 to continue acquiring screen image data and human eye attention data; If it is determined that there is no external light penetration device, execute step 4; Step 4: obtaining human eye status data, preprocessing the human eye status data, evaluating the preprocessed human eye status data, and obtaining a human eye discomfort evaluation value; Step 5: judging the discomfort of human eyes according to the result of obtaining the evaluation value of the discomfort of human eyes; Step 6: If it is determined that someone has eye discomfort, adjust the screen and return to step 4 to continue obtaining eye status data until it is determined that no one has eye discomfort; if it is determined that no one has eye discomfort, conduct a meteorological science demonstration.

2. The meteorological science popularization display method based on immersive technology according to claim 1, characterized in that: In step 1, set the detection time period; Filter and denoise the screen image data and human eye attention data; The screen image data includes pixel points, BGR color space, Lab value of pixel points, brightness value of pixel points and standard deviation of pixel points; The human eye attention data includes the eyeball contour position and the gaze point position; The image color difference, image brightness difference and image contrast difference are obtained by comprehensive analysis of screen image data; Normalizing the image color difference, image brightness difference and image contrast difference; The screen image abnormality coefficient is obtained according to the evaluation of the image color difference, image brightness difference and image contrast difference after normalization processing; Through comprehensive analysis of human eye attention data, the degree of eye saccade, the fixation time on the fixation point position, and the number of changes in the eye fixation point position during the detection period are obtained; Normalize the degree of saccades, the duration of fixation on the fixation point, and the number of changes in the fixation point during the detection period; The human eye inattention coefficient is obtained according to the normalized eye saccade degree, the fixation time on the fixation point position and the number of changes in the eye fixation point position during the detection period; The method for obtaining the external light entering the device evaluation value based on the evaluation of the screen image abnormality coefficient and the human eye inconcentration coefficient is as follows: Among them, WG represents the evaluation value of external light entering the device, PY represents the screen image abnormality coefficient, and RB represents the human eye inattention coefficient.

3. The meteorological science popularization display method based on immersive technology according to claim 2 is characterized in that: The specific steps of obtaining the image color difference, image brightness difference and image contrast difference through comprehensive analysis of screen image data are as follows: Using edge detection algorithm, the edge of pixel points is obtained and segmented, local areas are divided, and the area of ​​local areas is calculated; Using the color difference detection algorithm, the image is converted from the BGR color space to the Lab color space; The average Lab value of each local area is obtained by the Lab value of each local area pixel, and the difference between the Lab value of each local area pixel and the average Lab value of the local area is calculated; The absolute value results of the difference calculation are summed to obtain the color difference of the local area of ​​the image, and the color difference of each local area of ​​the image is summed to obtain the image color difference; Convert the image from Lab color space to gray image; Sum the brightness values ​​of the pixels in the local area; The sum of the brightness values ​​of the pixels in the local area is divided by the area of ​​the local area to obtain the average brightness value of the local area; The average brightness value of each local area is summed and averaged to obtain the average brightness value of the image; The average brightness value of each local area is calculated by subtracting the average brightness value of the image to obtain the brightness difference value; The absolute value of the brightness difference is summed to obtain the image brightness difference; The contrast of the pixel is obtained by the ratio of the standard deviation of each pixel in the local area to the average brightness value; The contrast of each pixel in the local area is summed and averaged to obtain the average contrast of the local area; The average contrast of each local area is summed and averaged to obtain the average contrast of the image; Calculate the difference between the average contrast of each local area and the average contrast of the image; The absolute value results of the difference calculation are summed to obtain the image contrast difference.

4. The meteorological science popularization display method based on immersive technology according to claim 2 is characterized in that: The specific steps of obtaining the degree of eye saccade, the fixation time on the fixation point position, and the number of changes in the eye fixation point position within the detection time period through comprehensive analysis of human eye attention data are as follows: In the initial stage of the detection period, the eyeball contour position is obtained by edge detection algorithm; During the detection period, the distance moved by the eyeball contour position, the number of times the eyeball contour position moves, and the direction of the eyeball contour position movement are obtained through the edge motion tracking algorithm; The saccade amplitude is obtained by calculating the absolute value of the distance difference of the eyeball contour position movement; The saccade frequency is obtained by the ratio of the number of eye contour position movements to the detection time period; The saccade angle is obtained by the absolute value of the angle difference in the direction of the eyeball contour position movement; The degree of saccade is obtained by multiplying the saccade amplitude, saccade frequency and saccade angle; The movement of the eyeball contour position is tracked by an edge motion tracking algorithm. When the eyeball contour position is stationary relative to the fixation point position, timing starts, and when the eyeball contour position moves, timing stops, thereby obtaining a single fixation time relative to the fixation point position. During the detection period, the sum of the fixation time of each fixation point position is calculated and then the fixation time of the fixation point position is obtained by averaging; S1: Set the fixation threshold according to the fixation time of the fixation point. During the detection period, when the fixation time of the eyeball on the fixation point is greater than or equal to the fixation threshold, it is regarded as the eyeball fixating on the fixation point. S2: Set the eye saccade threshold according to the degree of eye saccade. During the detection period, when the position of the eyeball contour moves each time and the next position is inconsistent with the previous position, it is regarded as the eyeball looking at other fixation points. The number of changes in the eye gaze point position during the detection time period is obtained based on S1 and S2.

5. The meteorological science popularization display method based on immersive technology according to claim 1 is characterized in that: In step 2, an external light penetration device threshold is set and compared with an external light entry device evaluation value; When the external light entering the device evaluation value is greater than or equal to the external light penetrating device threshold, it is determined that there is an external light penetrating device; When the external light entering the device evaluation value is less than the external light penetrating device threshold, it is determined that there is no external light penetrating device.

6. The meteorological science popularization display method based on immersive technology according to claim 1, characterized in that: In step 4, filtering and denoising are performed on the human eye state data; The human eye status data includes a human eye image, a human eye image frame number, an eyelid contour, an eyeball area, and an eyelid contour area; The degree of pupil constriction and eye closure are obtained by comprehensive analysis of the human eye status data after filtering and denoising; Normalize the pupil constriction and eye closure degree; The abnormal coefficient of human eye state is obtained according to the normalized pupil constriction and eye closure degree; The method for obtaining the human eye discomfort assessment value based on the human eye state abnormality coefficient and the human eye inconcentration coefficient is as follows: Among them, RP represents the human eye discomfort assessment value, RB represents the human eye unfocus coefficient, and ZY represents the human eye state abnormality coefficient.

7. The meteorological science popularization display method based on immersive technology according to claim 6 is characterized by: The specific steps of comprehensively analyzing the human eye state data after filtering and denoising to obtain the pupil constriction degree and the eye closure degree are as follows: The pupil area of ​​each frame of the human eye image is obtained by calculating the human eye image using the edge detection algorithm and the edge motion tracking algorithm; According to the number of human eye image frames, the pupil area of ​​each frame of the human eye image is summed and then averaged to obtain the average pupil area in the detection time period; Calculate the difference between the pupil area of ​​each frame of human eye image and the average pupil area during the detection time period; Using statistical principles, the pupil area threshold is set according to the average pupil area. When the result of the difference calculation is less than the pupil area threshold, the pupil area of ​​each frame of the human eye image is screened; Select all pupil areas of each frame of human eye images that meet the conditions, and sum the absolute values ​​of the differences between them and the average pupil area to obtain the pupil reduction degree; During the detection period, the movement trajectory of the eyelid contour is obtained using the edge detection algorithm and the edge motion tracking algorithm; When the area of ​​the eyelid contour increases to a stop and the area of ​​the eyeball decreases to a stop, the eye-closing threshold is set; when the area of ​​the eyelid contour decreases to a stop and the area of ​​the eyeball increases to a stop, the eye-opening threshold is set; The timer starts when the area of ​​the eyelid contour increases and stops, and the area of ​​the eyeball decreases and stops, and the timer stops when the area of ​​the eyelid contour decreases and the area of ​​the eyeball increases, and the eye closure duration is obtained; The duration of multiple eye closures within the detection period is summed and then averaged to obtain the duration of a single eye closure; Using statistical principles, the number of human eye images that meet the eye closing threshold within the detection period is counted to obtain the number of eye closing times within the detection period; When the area of ​​the eyelid contour and the area of ​​the eyeball are between the closed-eye threshold and the open-eye threshold, it indicates squinting; The area of ​​the eyelid contour of each frame of the human eye image when squinting is summed and then averaged to obtain the squinting range; The degree of eye closure is obtained by multiplying the duration of a single eye closure, the number of eye closures during the detection period, and the squinting range.

8. The meteorological science popularization display method based on immersive technology according to claim 1 is characterized by: In step 5, a human eye discomfort threshold is set and compared with the human eye discomfort assessment value; When the human eye discomfort assessment value is greater than or equal to the human eye discomfort threshold, it is judged that there is human eye discomfort; When the human eye discomfort evaluation value is less than the human eye discomfort threshold, it is determined that there is no human eye discomfort.

9. The meteorological science popularization display method based on immersive technology according to claim 1, characterized in that: The specific steps of adjusting the screen are: Reduce the screen brightness and contrast, and improve the clarity of the screen image until no one experiences eye discomfort.

10. A meteorological science popularization display system based on immersive technology, used in a meteorological science popularization display method based on immersive technology as claimed in any one of claims 1 to 9, characterized in that: include: Data acquisition module, data analysis module, data execution module and immersive module; The data acquisition module is used to acquire screen image data, human eye attention data and human eye status data and pre-process them, and send the pre-processed data to the data analysis module; The data analysis module is used to receive the data sent by the data acquisition module, analyze and judge the external light penetration device and the discomfort of the human eye, and send the judgment result to the data execution module; The data execution module is used to receive the judgment result of the data analysis module and execute the judgment result of the external light penetration device and the discomfort of the human eye; The immersive module includes an immersive device and a screen. The data execution module adjusts the immersive device and the screen according to the judgment result of the external light penetration device and the discomfort of the human eye.

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