Motion visual ability simulation evaluation method based on flying saucer shooting project characteristics

Abstract

The invention discloses a motion visual ability simulation evaluation method based on flying saucer shooting project characteristics, and belongs to the technical field of flying saucer shooting competitive ability and motion visual evaluation. A visual angle of an athlete is simulated to carry out scene shooting and video acquisition and processing of a disc target scene, the athlete is organized to wear an eye tracker to carry out visual ability test and evaluation, and a test report and an improvement direction are provided after evaluation; according to the method, the eye movement data can be comprehensively and accurately processed and analyzed, so that visual search mode indexes with scientific values are obtained, the advantages and disadvantages of athletes are analyzed, and scientific improvement directions and training strategies are provided.

Description

Technical Field

[0001] This invention belongs to the field of sports visual evaluation technology for skeet shooting competition, and particularly relates to a simulation evaluation method for sports visual ability based on the characteristics of skeet shooting. Background Technology

[0002] As a target-interception sport, visual ability is the most crucial core competitive element in skeet shooting. The processing of information related to visual stimuli during shooting includes the perception and identification of the target disc, visual tracking, and visual control. Whether in two-way or multi-directional skeet shooting, athletes need a comprehensive motion visual system to quickly and accurately detect the target's position and accurately perceive and judge its direction, distance, and speed.

[0003] However, due to the small size of the target and the high speed of the target in skeet shooting, the complexity of different events and positions in skeet shooting, and the significant impact of background information under real conditions, there is still a lack of effective evaluation methods for skeet shooting athletes. Previous basic optometry evaluations in the laboratory, such as letters and images, also had limitations such as a lack of visual indicators, limited evaluation content, and failure to truly and comprehensively reflect the motion visual characteristics of skeet shooting athletes.

[0004] Currently, eye-tracking technology is widely used in various sports. Eye-tracking devices can record athletes' fixation points, fixation durations, fixation shifts, and other eye-tracking indicators during the search process, effectively reflecting their cognitive accommodation activities. Previous studies have shown that elite athletes process visual information faster, with higher prediction accuracy and more agile reactions. In terms of eye-tracking characteristics, this manifests as higher visual search efficiency and more rational search strategies. It has also found some application in evaluating visual abilities in sports like tennis, badminton, and volleyball, such as skeet shooting. However, evaluating visual abilities in skeet shooting under real-world conditions is costly. Limited by current eye-tracking technology and the influence of variables such as lighting, wind, and weather, the stability and controllability of on-site visual ability assessments in skeet shooting are poor, and the reliability of the data is also affected. Therefore, the best approach is to obtain effective and reliable test results at the lowest cost through simulated assessments to reflect the visual ability characteristics of skeet shooting athletes. To address these issues, a simulation evaluation method for visual ability based on the characteristics of skeet shooting is urgently needed. Summary of the Invention

[0005] The purpose of this invention is to address the issue that while visual ability evaluation in sports like tennis, badminton, and volleyball has a certain application basis in similar events such as skeet shooting, the cost of evaluating visual ability in skeet shooting under real-world conditions is high. Furthermore, due to limitations in current eye-tracking technology and the influence of variables such as lighting, wind, and weather, the stability and controllability of on-site visual ability assessment in skeet shooting are poor, and the reliability of the data is also affected. Therefore, this invention proposes a motion visual ability simulation evaluation method based on the characteristics of skeet shooting.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a motion visual ability simulation evaluation method based on the characteristics of skeet shooting, comprising the following steps: S1. Select a scenario for simulating visual ability assessment; S2. Simulate the athlete's perspective to shoot and capture video of the target practice scene and process the video. S3. Organize athletes to wear eye trackers for visual ability testing and evaluation; S4. Provide a test report and improvement suggestions after the evaluation.

[0007] As a further description of the above technical solution: In step S1, the selected scenario for simulating visual ability evaluation identifies the key technical steps that require the most visual ability.

[0008] As a further description of the above technical solution: In S1, the key technical aspects of visual ability required are sorted out and classified, including: technical classification of the overall situation of skeet shooting, including a total of 8 positions, high and low platforms, single and double targets, and 135 variations of the target throwing spectrum of 5 positions and 9 targets in multi-directional skeet shooting; the key scenario selection for visual ability assessment requires athletes to have a longer time and space to track the skeet target, which is conducive to reflecting the athletes' visual characteristics.

[0009] As a further description of the above technical solution: In step S2, stimulus materials for the simulated evaluation of motor visual ability are collected and processed, and the scene of the disc target is captured and video is collected and processed from the perspective of an athlete.

[0010] As a further description of the above technical solution: In step S2, the acquisition and processing of stimulus materials for the simulated evaluation of motor visual ability includes: selecting the shooting equipment and setting parameters. This step requires a dedicated action camera, with shooting parameters set to manual and high-definition modes to complete the acquisition of information on a high-speed moving disc target. Since the disc target weighs between 105 and 110 grams, flies at speeds up to 30 m / s, has a diameter of 110 mm and a thickness of 25 mm, is small in size, and is located in an open outdoor environment, the camera shutter speed must be at least 1 / 1000, the resolution above 4K, the frame rate 50 fps, and automatic white balance used. Clear capture is essential for recording; a shooting plan must be determined, and the shooting environment and conditions must be controlled. The shooting height should be as close as possible to the shooting athlete's line of sight, and the camera should be placed in the center of the target position to ensure that the perspective and presentation of the video stimulus material are relatively consistent with the athlete's viewing effect on the target; the collection time should be between 3 and 5 pm, when the lighting is relatively soft and the wind speed is below level 3 to ensure the stability of the disc target's flight trajectory and to ensure the best collection effect; during the recording process, the athlete should watch the video in real time next to the experimenter to confirm that the visual effect of the video matches the viewing perspective on the target.

[0011] As a further description of the above technical solution: In step S3, athletes wear eye trackers and undergo visual ability testing and evaluation in accordance with the testing procedures, including calibration, standardized testing conditions, and operational procedures.

[0012] As a further description of the above technical solution: In S3, the simulated evaluation of motor visual ability includes: selecting a well-lit, isolated, and soundproof testing environment; arranging and preparing testing equipment, including a glasses-type eye tracker with a binocular sampling rate of 120Hz, a resolution of 1280×720@30fps, a tracking field of view of 80° horizontally and 60° vertically, and a fixation accuracy of 0.5°; using a three-dimensional eye-tracking algorithm and an automatic parallax compensation algorithm to calculate fixation point data; capturing the subject's eye movement data while simultaneously recording scene images and eye images; and presenting the stimulus material by projecting video material onto a large, adjustable screen display (55 inches, 1210×685mm, resolution 1920×1080, brightness ≥350cd / m²) via a laptop computer. 2The recording software is required to record the visual data of the skeet shooting athlete in real time while watching the video of the skeet target in flight. The test process includes a preparation phase and a test phase. In the preparation phase, the athlete's basic position is 1.5m in front of the large screen monitor. The height of the monitor is adjusted so that the center point of the screen is level with the athlete's line of sight, so as to fully simulate the athlete's daily target viewing angle and achieve the best simulation test effect. In terms of wearing and calibrating the test equipment, the test personnel help the skeet shooting athlete wear the eye tracker to ensure that the glasses are in a comfortable position and that the eye tracker completes the capture and correction of the pupil position through calibration. In the pre-test phase, the athlete needs to be guided to read the test instructions before the test begins to fully understand the content and purpose of the test, and the test can begin with the athlete's permission. To ensure the smooth conduct of the test, two sets of videos were played first for athletes to conduct a pre-test, ensuring they were familiar with the testing environment and procedures. During the formal test, athletes stood in front of a computer screen and watched randomly played videos of previously collected and processed disc targets flying. When a disc target flew out, the athlete had to react by pressing the space bar to reflect their sensitivity and reaction speed to the target. If no action was taken by the end of the stimulus material, the next video would be played directly. After each video, a 1500ms interval was provided for the participants to rest, buffer, and prepare for the next test stimulus. A "+" sign was displayed after each video segment to ensure that the participant's line of sight remained within the optimal recording range of the central field of view at the start of the test.

[0013] As a further description of the above technical solution: In S4, the data processing after the evaluation and the visualization index output of the visual search mode are compared to the differences in quantitative indicators of athletes at different levels, and test reports and directions for improvement are provided.

[0014] As a further description of the above technical solution: In S4, the post-assessment data processing and visual ability index output includes the following steps: data processing and analysis; index generation and report writing feedback; the data processing stage includes data preprocessing to ensure the quality of eye-tracking data. First, a low-pass filter or moving average filter is used to remove high-frequency noise, ensuring appropriate filter parameter settings to avoid excessive smoothing leading to loss of effective information. Second, error correction: after the test, the calibration tool provided by the eye tracker is used to correct the data, requiring the subject to keep their head fixed; the accuracy of the fixation calibration point directly affects the calibration result. Third, data smoothing: generally, smoothing algorithms such as Kalman filtering are used to reduce data fluctuations; this process requires selecting appropriate smoothing parameters to ensure that the smoothed data still accurately reflects the eye movement trajectory; recognition Fixation and saccades are also core steps in eye-tracking data processing. First, fixation identification uses the I-VT (Identification by Velocity-Threshold) algorithm, determining fixations based on eye movement velocity. Velocities below a certain threshold are considered fixations. The common steps are: 1) calculating the eye movement velocity between every two consecutive data points; 2) marking consecutive data points with velocities below the threshold as fixations; and 3) calculating the average position of these data points as the fixation location. This process requires selecting an appropriate velocity threshold; too high or too low a threshold will affect the accuracy of identification. Second, saccade recognition also identifies saccades based on high-speed movement between fixations. The steps involve, after identifying the fixation point, calculating the velocity between the fixation points... When the movement speed exceeds a certain threshold, it is considered a saccade, and the start and end points of the saccade are recorded. Saccade recognition needs to be combined with fixation point recognition to distinguish between fixation and saccades. In the data analysis stage, in-depth statistical analysis is performed on the processed eye movement data, including fixation point and saccade path analysis. Fixation point analysis first calculates the average fixation time: calculating the duration of each fixation point and calculating the average; fixation point count: counting the total number of fixations in each experimental task; fixation distribution: analyzing the spatial distribution of fixations on visual stimuli and generating heatmaps. Saccade analysis includes two aspects: saccade length: calculating the path length of each saccade and analyzing the saccade length distribution under different tasks; and saccade direction: statistically analyzing the directional distribution of saccades. Subjects' visual search direction preferences; reaction time, also known as target recognition time: measuring the time from the start of the task to the subject's first fixation on the target, which can be used to analyze the differences in reaction time under different tasks; pattern recognition, including the use of advanced algorithms to identify and classify visual search patterns: one is clustering analysis methods: using clustering algorithms such as K-means and DBSCAN to classify similar fixation points and saccade paths into several categories; the steps are: first, extracting the features of each fixation point and saccade; second, selecting appropriate clustering algorithms and parameters to perform clustering analysis; finally, analyzing the features of different categories to identify common visual search patterns; the main method of heatmap analysis is: generating heatmaps of fixation point distribution to visually display the high-frequency areas of fixation;The steps are as follows: First, all fixations in the experimental task are overlaid on the stimulus image; second, a color gradient is used to represent the density of fixations, generating a heatmap; in application, heatmap analysis is used to identify hotspot areas of visual search and analyze differences in search patterns under different tasks or conditions; in terms of output indicators, indicators need to be selected according to the research purpose. Fixation indicators include average fixation time, which reflects the length of time the subject stays at each location; number of fixations, which reflects the total number of fixations the subject has in the task; saccade indicators include saccade path length, which reflects the total distance of eye movement during the search; saccade direction, which can analyze saccade direction preferences and understand visual search strategies; and reaction time, which measures the time required for the subject to identify the target, reflecting reaction speed; the results analysis and report writing after indicator generation are presented in various forms, including charts and bar graphs to display indicators such as average fixation time and number of fixations under different tasks; line graphs to show the trend of reaction time changes under different tasks; and heatmaps to display the distribution of fixations and analyze visual search hotspot areas under different tasks.

[0015] As a further description of the above technical solution: In S4, the statistical table can summarize the statistical results and list the statistical results of each indicator, including the mean and standard deviation. The report should explain the analysis results in detail, discuss the discovered visual search patterns and their significance, and propose suggestions for further research.

[0016] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: In this invention, the method can comprehensively and accurately process and analyze eye-tracking data, thereby deriving scientifically valuable visual search pattern indicators, analyzing athletes' strengths and weaknesses, and providing scientific directions for improvement and training strategies. Attached Figure Description

[0017] Figure 1 This is a flowchart of a motion vision ability simulation evaluation method based on the characteristics of skeet shooting. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Please see Figure 1 This invention provides a technical solution: a method for simulating and evaluating motion visual ability based on the characteristics of skeet shooting, comprising the following steps: S1. Select the scenario for simulating visual ability assessment and identify the key technical aspects that require the most visual ability. The key technical aspects of the required visual ability are sorted out and classified, including: technical classification of the overall situation of the skeet shooting event. The double skeet includes a total of 8 positions, high and low platform single and double targets, and 135 variations of the target throwing pattern of the multi-directional skeet with 5 positions and 9 targets. The key scenario selection for visual ability assessment requires athletes to have a longer time and space to track the skeet target, which is conducive to reflecting the athletes' visual characteristics. S2. Acquisition and processing of stimulus materials for simulated assessment of motor visual ability: Simulating the athlete's perspective to conduct scenario-based filming and video acquisition and processing of the disc target. Acquisition and processing of stimulus materials for simulated assessment of motor visual ability includes: selecting filming equipment and setting parameters. This step requires a dedicated action camera, with filming parameters set to manual and high-definition modes to complete the acquisition of information from the high-speed moving disc target. Because the disc target weighs between 105 and 110 grams, flies at speeds up to 30 m / s, has a diameter of 110 mm and a thickness of 25 mm, is small in size, and is located in an open outdoor environment, the camera shutter speed must be at least 1 / 1000. For clear recording, a resolution of 4K or higher and a frame rate of 50fps with automatic white balance are required. The shooting plan must be determined, and the shooting environment and conditions controlled. The shooting height should be as close as possible to the shooting athlete's line of sight, and the camera should be placed in the center of the target position to ensure that the perspective and presentation of the stimulus material in the recorded video are relatively consistent with the athlete's viewing experience. The recording time is from 3-5 pm, with relatively soft lighting and wind speeds below level 3, to ensure the stability of the disc target's flight trajectory and the best recording results. During the recording process, the athlete watches the video in real-time next to the experimenter to confirm that the visual effect of the recorded video matches the viewing angle. S3. Organize athletes to wear eye trackers and conduct visual ability tests and evaluations according to the test procedures, including calibration, standardized testing conditions, and operational procedures. This includes conducting simulated motion visual ability evaluations, such as selecting a well-lit, isolated, and soundproofed testing environment; arranging and preparing testing equipment, including selecting a glasses-type eye tracker with a binocular sampling rate of 120Hz, a resolution of 1280×720@30fps, a tracking field of view of 80° horizontally and 60° vertically, and a fixation accuracy of 0.5°. A 3D eye-tracking algorithm and an automatic parallax compensation algorithm are used to calculate fixation point data, capturing the experimenter's eye movement data while simultaneously recording scene images and eye images; for the presentation of stimulus materials, video materials need to be projected onto a large, adjustable screen monitor (55 inches, display size 1210×685mm), with a resolution of 1920×1080 and a brightness ≥350cd / m². 2The recording software is required to record the visual data of the skeet shooting athlete in real time while watching the video of the skeet target in flight. The test process includes a preparation phase and a test phase. In the preparation phase, the athlete's basic position is 1.5m in front of the large screen monitor. The height of the monitor is adjusted so that the center point of the screen is level with the athlete's line of sight, so as to fully simulate the athlete's daily target viewing angle and achieve the best simulation test effect. In terms of wearing and calibrating the test equipment, the test personnel help the skeet shooting athlete wear the eye tracker to ensure that the glasses are in a comfortable position and that the eye tracker completes the capture and correction of the pupil position through calibration. In the pre-test phase, the athlete needs to be guided to read the test instructions before the test begins to fully understand the content and purpose of the test, and the test can begin with the athlete's permission. To ensure the smooth conduct of the test, two sets of videos were played first for athletes to conduct a pre-test, ensuring that they were adapted to the testing environment and fully familiar with the testing procedures. During the formal test, athletes stood in front of the computer screen and watched randomly played videos of previously collected and processed disc targets flying. When the disc target flew out, athletes had to react by pressing the space bar to reflect their sensitivity to the target and their reaction speed. If no action was taken by the end of the stimulus material, the next video would be played directly. After each video was played, a 1500ms interval was arranged to allow the subjects to rest and prepare for the next test stimulus material. A "+" would be displayed after each video to ensure that the subjects' line of sight remained within the optimal recording range of the central field of view at the start of the test. S4. Post-assessment data processing and visualization of visual search patterns, comparing quantitative differences among athletes of different levels, providing test reports and improvement directions. Post-assessment data processing and visual ability indicator output include the following steps: data processing and analysis; indicator generation and report writing feedback. The data processing stage includes data preprocessing to ensure eye-tracking data quality: first, using low-pass filters or moving average filters to remove high-frequency noise, ensuring appropriate filter parameter settings to avoid over-smoothing leading to loss of effective information; second, error correction: after testing, using the calibration tool provided by the eye tracker to correct the data, requiring the subject to keep their head fixed, as the accuracy of the fixation calibration point directly affects the calibration results; third, data smoothing: generally using flattening... Smoothing algorithms, such as Kalman filtering, reduce data fluctuations. This process requires selecting appropriate smoothing parameters to ensure that the smoothed data still accurately reflects the eye movement trajectory. Identifying fixation points and saccades are also core steps in eye-tracking data processing: First, fixation point identification uses the I-VT (Identification by Velocity-Threshold) algorithm to determine fixation points based on eye movement velocity; a velocity below a certain threshold is considered a fixation. Common steps include: first, calculating the eye movement velocity between every two consecutive data points; second, marking consecutive data points with velocities below the threshold as fixation points; and third, calculating the average position of these data points as the fixation point's location. This process requires selecting an appropriate velocity threshold; too high or too low a threshold will affect the accuracy of the data. The accuracy of saccade recognition is crucial; secondly, saccade recognition also identifies saccades based on the high-speed movement between fixation points. The steps involve identifying the fixation point, calculating the movement speed between fixation points, and recording the start and end points of the saccade when the speed exceeds a certain threshold. Saccade recognition requires combining saccade identification with fixation point identification to distinguish between fixation and saccades. In the data analysis stage, in-depth statistical analysis is performed on the processed eye movement data, including fixation point and saccade path analysis. Fixation point analysis first calculates the average fixation time: calculating the duration of each fixation point and calculating the average; the number of fixation points: counting the total number of fixation points in each experimental task; fixation distribution: analyzing the spatial distribution of fixation points on visual stimuli and generating a heatmap; saccades... The analysis includes two main aspects: First, saccade length: calculating the path length of each saccade and analyzing the distribution of saccade length under different tasks; second, saccade direction: statistically analyzing the directional distribution of saccades and the subject's visual search directional preferences; third, reaction time, also known as target recognition time: measuring the time from the start of the task to the subject's first fixation on the target, which can be used to analyze the differences in reaction time under different tasks; and fourth, pattern recognition, including the use of advanced algorithms to identify and classify visual search patterns: one is clustering analysis methods: using clustering algorithms such as K-means and DBSCAN to classify similar fixation points and saccade paths into several categories; the steps are: first, extracting the features of each fixation point and saccade; second, selecting appropriate clustering algorithms and parameters to perform clustering analysis.Finally, the characteristics of different categories are analyzed to identify common visual search patterns. The heatmap analysis method mainly involves generating a heatmap of fixation point distribution to visually display high-frequency fixation areas. The steps are: first, overlaying all fixations from the experimental task onto the stimulus image; second, using color gradients to represent the density of fixations to generate a heatmap. In application, heatmap analysis identifies hotspot areas of visual search and analyzes differences in search patterns under different tasks or conditions. Regarding output metrics, the selection of metrics must first be based on the research objective. Fixation metrics include average fixation time, reflecting the length of time a subject spends at each location; the number of fixations, reflecting the total number of fixations a subject uses in the task; and saccade metrics, including saccade path length, reflecting the subject's... The total distance of eye movements during the search process; saccadic direction analysis to understand saccadic direction preferences and visual search strategies; reaction time to measure the time required for a subject to recognize a target, reflecting reaction speed; the results analysis and report writing after the indicators are generated are presented in various forms, including charts and bar graphs to show indicators such as average fixation time and number of fixations under different tasks; line graphs to show the trend of reaction time changes under different tasks; heatmaps to show the distribution of fixations and analyze visual search hotspots under different tasks; statistical tables to summarize the statistical results and list the statistical results of various indicators, including the mean and standard deviation; the report writing needs to explain the analysis results in detail, discuss the discovered visual search patterns and their significance, and propose suggestions for further research.

[0020] In this embodiment, the method can comprehensively and accurately process and analyze eye-tracking data, thereby deriving scientifically valuable visual search pattern indicators, analyzing athletes' strengths and weaknesses, and providing scientific directions for improvement and training strategies.

[0021] Example 2 Please see Figure 1 The present invention provides another technical solution: a motion visual ability simulation evaluation system and method based on the characteristics of skeet shooting, comprising the following steps: Step (1) First, select the scenario for simulating visual ability assessment: Since the key technical aspects of skeet shooting in different projects are different, it is necessary to first identify the key technical aspects and scenarios that require the most visual ability through expert interviews and other means.

[0022] Step (2) involves collecting and processing stimulus materials for the simulated evaluation of motor visual ability: based on the confirmation of key technical scenarios, the on-site shooting and video acquisition and processing of the disc target are carried out from the perspective of the athlete.

[0023] Step (3) involves organizing a simulated assessment of athletic visual abilities, where athletes wear eye trackers and undergo visual ability testing and evaluation in accordance with the testing procedures, standardized testing conditions, and operational procedures.

[0024] Step (4) involves data processing and visualization of the visual search pattern after the evaluation, comparing the differences in quantitative indicators among athletes of different levels, and providing test reports and directions for improvement.

[0025] Furthermore, step (1) selects the scenario for simulating visual ability assessment, including: Based on the dimensions of technology classification, different scenarios of different projects were categorized. There were 8 positions for the bidirectional flying saucer, 4 target launching methods (high and low platforms, single and double targets), and the shooting process included 6 technical segments. The multi-directional flying saucer had many variations in height (1-4m) and angle (0-45°), with 135 variations across 9 target launching patterns, and the shooting process consisted of 5 segments. After analyzing the different technical aspects and segments, expert interviews were conducted to identify the key scenarios that most required visual abilities, which served as the basis for collecting experimental stimulus materials.

[0026] The key requirements for selecting scenarios in visual ability assessment not only require athletes to have a longer time and spatial range to track the disc target, so as to reflect the athletes' visual characteristics, but also need to fully reflect the typicality and representativeness of the athletes' technical level.

[0027] Furthermore, step (2), acquiring and processing stimulus materials for the simulated assessment of motor visual ability, includes the following steps: 1) Select shooting equipment and parameter settings. Use a dedicated action camera from brands such as SONY AX700. Set the shooting parameters to manual and HD modes. The specific requirements for capturing high-speed moving disc targets are: shutter speed 1 / 1000, resolution 4K, frame rate 50fps, and automatic white balance.

[0028] 2) Determine the shooting plan and control the shooting environment and conditions. Based on the athletes' height statistics, select shooting athletes within the median height range. Determine the camera shooting height (ideally at the same level as the shooting athlete's line of sight). Place the camera at the center of the target position to ensure that the perspective and presentation of the video stimulus material are relatively consistent with the athlete's viewing experience. Generally, video recording time is between 3-5 pm, when the sunlight is relatively soft and the wind speed is below level 3, ensuring a stable target flight trajectory for optimal data acquisition. During recording, the athlete watches the video in real-time next to the experimenter to confirm that the visual effect of the video matches the target viewing perspective. Referring to the stimulus material item design scheme of previous studies, record at least 20 videos under different conditions.

[0029] 3) Screening and processing of video stimulus materials. The videos taken were further screened by experts such as coaches and skeet shooting referees to select the most suitable videos. During the screening, video materials with interference factors such as certain deviations in the flying speed and trajectory of the target disc were removed, so as to ensure that the video tasks maximally conform to the visual effects of the target disc flying in the real shooting process of the athletes. Use video editing software to edit and process all videos, and the processed videos need to be approved by professional athletes, coaches and sports psychology experts.

[0030] Furthermore, step (3) adopts an organization to conduct a simulated evaluation of sports visual ability, including the following steps: Test environment: Sufficient light, the room is independent and airtight, and the sound insulation effect is good.

[0031] Arrangement and preparation of test instruments Eye tracker selection and configuration: A glasses-type eye tracker with a binocular sampling rate of 120Hz, a resolution of 1280×720@30fps, a tracking viewing angle range of 80° horizontally and 60° vertically, and a fixation accuracy of 0.5°. Use a three-dimensional eye tracking algorithm and an automatic parallax compensation algorithm to obtain fixation point data, capture the eye movement data of the experimenter, and record the scene image and eye image at the same time. Presentation of stimulus materials: The video stimulus materials are projected onto a liftable HuShida large-screen monitor through a laptop computer. The screen size is 55 inches (display size is 1210×685mm), the resolution is 1920×1080, and the brightness ≥ 350cd / m2.

[0032] Recording software: The research uses the software supporting the eye tracker to record the visual data of skeet shooting athletes during the process of watching the video of the target disc flying and perform post-processing.

[0033] 3) Test process: ① Preparation stage: Basic position: First, let the test athlete stand 1.5m in front of the large-screen monitor, and adjust the height of the display screen until the center point of the screen is level with the athlete's line of sight, so as to fully simulate the athlete's daily view of the target and achieve the best simulation test effect.

[0034] Wearing and calibration of test instruments: The test personnel help the tested skeet shooting athlete wear the eye movement instrument, ensure that the glasses are in a comfortable position, and complete the capture and calibration of the pupil position through calibration of the eye movement instrument.

[0035] ② Test stage: Pre-test: Before the test starts, guide the tester to read the experiment introduction, fully understand the content and purpose of the experiment, and start the experiment with the permission of the athlete. To ensure the smooth progress of the test, first play two groups of videos for the athlete to conduct a pre-test to ensure that the athlete adapts to the test environment and is fully familiar with the test process.

[0036] Formal Testing: With preliminary preparations complete, the formal testing begins. Athletes stand in front of a computer screen and watch randomly played videos of previously collected and processed disc targets flying. When a disc is launched, the athlete must react by pressing the spacebar to assess their sensitivity and reaction speed. If no action is taken by the end of the stimulus, the next video is played. A 1500ms interval is provided between each video to allow participants to rest, buffer, and prepare for the next stimulus. A "+" sign appears after each video segment to ensure the participant's gaze remains within the optimal recording range of the central field of view at the start of the test.

[0037] Furthermore, the data processing and visual ability index output after step (4) includes the following steps: Data processing stage ① Data preprocessing to ensure eye-tracking data quality: First, low-pass filters or moving average filters are used to remove high-frequency noise, ensuring appropriate filter parameter settings to avoid over-smoothing that could lead to loss of useful information. Second, error correction: After testing, the data is corrected using the calibration tool provided by the eye tracker. Subjects are required to keep their heads fixed, as the accuracy of the fixation calibration point directly affects the calibration results. Third, data smoothing: Smoothing algorithms such as Kalman filtering are generally used to reduce data fluctuations. This process requires selecting appropriate smoothing parameters to ensure that the smoothed data still accurately reflects the eye movement trajectory.

[0038] ② Identifying fixations and saccades are core steps in eye-tracking data processing: Fixation identification uses the I-VT (Identification by Velocity-Threshold) algorithm, which determines fixations based on eye movement velocity. Velocity below a certain threshold is considered fixation. The common steps are: first, calculate the eye movement velocity between every two consecutive data points; second, mark consecutive data points with velocities below the threshold as fixations; and third, calculate the average position of these data points as the fixation location. This process requires selecting an appropriate velocity threshold; too high or too low a threshold will affect the accuracy of identification. Secondly, saccade identification also identifies saccades based on high-speed movement between fixations. The steps involve identifying fixations, calculating the movement velocity between them, and recording the start and end points of saccades when the velocity exceeds a certain threshold. Satcade identification needs to combine saccade identification with fixation identification to distinguish between fixation and saccades.

[0039] Data analysis stage ① Conduct in-depth statistical analysis on the processed eye-tracking data. Fixation analysis: First, the average fixation time, i.e., the duration of each fixation point, is calculated as an average. Number of fixations: The total number of fixations in each experimental task is counted. Fixation distribution: The spatial distribution of fixations on visual stimuli is analyzed, and a heatmap is generated.

[0040] Saccade analysis involves two main aspects: First, calculating the path length for each saccade and analyzing the distribution of saccade length under different tasks. Second, analyzing saccade direction: statistically analyzing the directional distribution of saccades and the directional preferences of subjects' visual searches.

[0041] Reaction time, also known as target recognition time, measures the time from the start of a task to the subject's first gaze at the target, and can be used to analyze differences in reaction time across different tasks.

[0042] ② The pattern recognition stage includes using advanced algorithms to identify and classify visual search patterns: One approach is clustering analysis: using clustering algorithms such as K-means and DBSCAN, similar gaze points and saccade paths are grouped into several categories. The steps are as follows: First, extract the features of each gaze point and saccade (such as location, duration, and path length). Second, select an appropriate clustering algorithm and parameters to perform clustering analysis. Finally, analyze the features of different categories to identify common visual search patterns.

[0043] The main method of heatmap analysis is to generate a heatmap of fixation point distribution, visually displaying high-frequency areas of fixation. The steps are as follows: First, all fixations from the experimental task are overlaid on the stimulus image. Second, a color gradient is used to represent the density of fixations, generating a heatmap. In applications, heatmap analysis is used to identify hotspots in visual search and analyze differences in search patterns under different tasks or conditions.

[0044] Indicator output stage ①Indicator selection Regarding output metrics, the first step is to select metrics based on the research objective. For eye-tracking, metrics reflecting the visual abilities of skeet shooting athletes are generally defined as visual search patterns—the search methods athletes use to gather useful information by observing the moving scene. Typical metrics representing visual search patterns include fixation count, fixation duration, saccade distance, and the fixation trajectory formed by connecting the coordinates of various fixation points. Fixation metrics include average fixation time, reflecting the length of time the subject spends at each location; the number of fixation points, reflecting the total number of fixation points the subject uses during the task; saccade distance metrics include saccade path length, reflecting the total distance the subject's eyes travel during the search; saccade direction, which analyzes saccade direction preferences and reveals visual search strategies; and reaction time, which measures the time required for the subject to identify the target.

[0045] To accurately grasp the information from stimuli, athletes need to maintain a certain eye position to project the information onto their retina; this series of processes is called fixation. The number of fixations and fixation duration reflect the temporal characteristics of an athlete's visual search, which are closely related to decision-making reaction time and accuracy in task situations, reflecting the efficiency of the athlete's visual information processing. Sagging distance and the fixation trajectory formed by connecting the coordinates of fixation points reflect the spatial characteristics of an athlete's visual search, and are related to the athlete's main processing mechanisms for acquiring effective information.

[0046] ② Results Analysis and Report Writing Feedback The results analysis and report writing after indicator generation can be presented in various formats, including charts and bar graphs to display indicators such as average fixation time and number of fixations under different tasks; line graphs to show the trend of reaction time changes under different tasks; heatmaps to show the distribution of fixations and analyze visual search hotspots under different tasks; and statistical tables to summarize the statistical results and list the statistical results of each indicator, including the mean and standard deviation. The report writing should explain the analysis results in detail, discuss the discovered visual search patterns and their significance, and propose suggestions for further research. Through these detailed steps, eye-tracking data can be comprehensively and accurately processed and analyzed to derive scientifically valuable visual search pattern indicators, analyze athletes' strengths and weaknesses, and provide scientific directions for improvement and training guidance strategies.

[0047] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for simulating and evaluating motion visual ability based on the characteristics of skeet shooting, characterized in that: Includes the following steps: S1. Select a scenario for simulating visual ability assessment; S2. Simulate the athlete's perspective to shoot and capture video of the target practice scene and process the video. S3. Organize athletes to wear eye trackers for visual ability testing and evaluation; S4. Provide a test report and improvement suggestions after the evaluation.

2. The method for simulating and evaluating motion visual ability based on the characteristics of skeet shooting as described in claim 1, characterized in that, In step S1, the selected scenario for simulating visual ability evaluation identifies the key technical steps that require the most visual ability.

3. The method for simulating and evaluating motion visual ability based on the characteristics of skeet shooting as described in claim 2, characterized in that, In S1, the key technical aspects of visual ability required are sorted out and classified, including: technical classification of the overall situation of skeet shooting, including a total of 8 positions, high and low platforms, single and double targets, and 135 variations of the target throwing spectrum of 5 positions and 9 targets in multi-directional skeet shooting; the key scenario selection for visual ability assessment requires athletes to have a longer time and space to track the skeet target, which is conducive to reflecting the athletes' visual characteristics.

4. The method for simulating and evaluating motion visual ability based on the characteristics of skeet shooting as described in claim 1, characterized in that, In step S2, stimulus materials for the simulated evaluation of motor visual ability are collected and processed, and the scene of the disc target is captured and video is collected and processed from the perspective of an athlete.

5. The method for simulating and evaluating motion visual ability based on the characteristics of skeet shooting as described in claim 4, characterized in that, In step S2, the acquisition and processing of stimulus materials for the simulated evaluation of motor visual ability includes: selecting the shooting equipment and setting parameters. This step requires a dedicated action camera, with shooting parameters set to manual and high-definition modes to complete the acquisition of information on a high-speed moving disc target. Since the disc target weighs between 105 and 110 grams, flies at speeds up to 30 m / s, has a diameter of 110 mm and a thickness of 25 mm, is small in size, and is located in an open outdoor environment, the camera shutter speed must be at least 1 / 1000, the resolution above 4K, the frame rate 50 fps, and automatic white balance used. Clear capture is essential for recording; a shooting plan must be determined, and the shooting environment and conditions must be controlled. The shooting height should be as close as possible to the shooting athlete's line of sight, and the camera should be placed in the center of the target position to ensure that the perspective and presentation of the video stimulus material are relatively consistent with the athlete's viewing effect on the target; the collection time should be between 3 and 5 pm, when the lighting is relatively soft and the wind speed is below level 3 to ensure the stability of the disc target's flight trajectory and to ensure the best collection effect; during the recording process, the athlete should watch the video in real time next to the experimenter to confirm that the visual effect of the video matches the viewing perspective on the target.

6. The method for simulating and evaluating motion visual ability based on the characteristics of skeet shooting as described in claim 1, characterized in that, In step S3, athletes wear eye trackers and undergo visual ability testing and evaluation in accordance with the testing procedures, including calibration, standardized testing conditions, and operational procedures.

7. The method for simulating and evaluating motion visual ability based on the characteristics of skeet shooting as described in claim 6, characterized in that, In S3, the simulated evaluation of motor visual ability includes: selecting a well-lit, isolated, and soundproof testing environment; arranging and preparing testing equipment, including a glasses-type eye tracker with a binocular sampling rate of 120Hz, a resolution of 1280×720@30fps, a tracking field of view of 80° horizontally and 60° vertically, and a fixation accuracy of 0.5°; using a three-dimensional eye-tracking algorithm and an automatic parallax compensation algorithm to calculate fixation point data; capturing the subject's eye movement data while simultaneously recording scene images and eye images; and presenting the stimulus material by projecting video material onto a large, adjustable screen display (55 inches, 1210×685mm, resolution 1920×1080, brightness ≥350cd / m²) via a laptop computer. 2 The recording software is required to record the visual data of the skeet shooting athlete in real time while watching the video of the skeet target in flight. The test process includes a preparation phase and a test phase. In the preparation phase, the athlete's basic position is 1.5m in front of the large screen monitor. The height of the monitor is adjusted so that the center point of the screen is level with the athlete's line of sight, so as to fully simulate the athlete's daily target viewing angle and achieve the best simulation test effect. In terms of wearing and calibrating the test equipment, the test personnel help the skeet shooting athlete wear the eye tracker to ensure that the glasses are in a comfortable position and that the eye tracker completes the capture and correction of the pupil position through calibration. In the pre-test phase, the athlete needs to be guided to read the test instructions before the test begins to fully understand the content and purpose of the test, and the test can begin with the athlete's permission. To ensure the smooth conduct of the test, two sets of videos were played first for athletes to conduct a pre-test, ensuring they were familiar with the testing environment and procedures. During the formal test, athletes stood in front of a computer screen and watched randomly played videos of previously collected and processed disc targets flying. When the disc target flew out, athletes had to react by pressing the space bar to reflect their sensitivity and reaction speed to the target. If no action was taken by the end of the stimulus, the next video would be played directly. After each video, a 1500ms interval was provided for the participants to rest, buffer, and prepare for the next stimulus. A "+" sign was displayed after each video to ensure that the participants' gaze remained within the optimal recording range of the central field of view at the start of the test.

8. The method for simulating and evaluating motion visual ability based on the characteristics of skeet shooting as described in claim 1, characterized in that, In S4, the data processing after the evaluation and the visualization index output of the visual search mode are compared to the differences in quantitative indicators of athletes at different levels, and test reports and directions for improvement are provided.

9. The method for simulating and evaluating motion visual ability based on the characteristics of skeet shooting as described in claim 8, characterized in that, In S4, the post-assessment data processing and visual ability index output includes the following steps: data processing and analysis; index generation and report writing feedback; the data processing stage includes data preprocessing to ensure the quality of eye-tracking data. First, a low-pass filter or moving average filter is used to remove high-frequency noise, ensuring appropriate filter parameter settings to avoid excessive smoothing leading to loss of effective information. Second, error correction: after the test, the calibration tool provided by the eye tracker is used to correct the data, requiring the subject to keep their head fixed; the accuracy of the fixation calibration point directly affects the calibration result. Third, data smoothing: generally, smoothing algorithms such as Kalman filtering are used to reduce data fluctuations; this process requires selecting appropriate smoothing parameters to ensure that the smoothed data still accurately reflects the eye movement trajectory; recognition Fixation and saccades are also core steps in eye-tracking data processing. First, fixation identification uses the I-VT (Identification by Velocity-Threshold) algorithm, determining fixations based on eye movement velocity. Velocities below a certain threshold are considered fixations. The common steps are: 1) calculating the eye movement velocity between every two consecutive data points; 2) marking consecutive data points with velocities below the threshold as fixations; and 3) calculating the average position of these data points as the fixation location. This process requires selecting an appropriate velocity threshold; too high or too low a threshold will affect the accuracy of identification. Second, saccade recognition also identifies saccades based on high-speed movement between fixations. The steps involve, after identifying the fixation point, calculating the velocity between the fixation points... When the movement speed exceeds a certain threshold, it is considered a saccade, and the start and end points of the saccade are recorded. Saccade recognition needs to be combined with fixation point recognition to distinguish between fixation and saccades. In the data analysis stage, in-depth statistical analysis is performed on the processed eye movement data, including fixation point and saccade path analysis. Fixation point analysis first calculates the average fixation time: calculating the duration of each fixation point and calculating the average; fixation point count: counting the total number of fixations in each experimental task; fixation distribution: analyzing the spatial distribution of fixations on visual stimuli and generating heatmaps. Saccade analysis includes two aspects: saccade length: calculating the path length of each saccade and analyzing the saccade length distribution under different tasks; and saccade direction: statistically analyzing the directional distribution of saccades. Subjects' visual search direction preferences; reaction time, also known as target recognition time: measuring the time from the start of the task to the subject's first fixation on the target, which can be used to analyze the differences in reaction time under different tasks; pattern recognition, including the use of advanced algorithms to identify and classify visual search patterns: one is clustering analysis methods: using clustering algorithms such as K-means and DBSCAN to classify similar fixation points and saccade paths into several categories; the steps are: first, extracting the features of each fixation point and saccade; second, selecting appropriate clustering algorithms and parameters to perform clustering analysis; finally, analyzing the features of different categories to identify common visual search patterns; the main method of heatmap analysis is: generating heatmaps of fixation point distribution to visually display the high-frequency areas of fixation;The steps are as follows: First, all fixations in the experimental task are overlaid on the stimulus image; second, a color gradient is used to represent the density of fixations, generating a heatmap; in application, heatmap analysis is used to identify hotspot areas of visual search and analyze differences in search patterns under different tasks or conditions; in terms of output indicators, indicators need to be selected according to the research purpose. Fixation indicators include average fixation time, which reflects the length of time the subject stays at each location; number of fixations, which reflects the total number of fixations the subject has in the task; saccade indicators include saccade path length, which reflects the total distance of eye movement during the search; saccade direction, which can analyze saccade direction preferences and understand visual search strategies; and reaction time, which measures the time required for the subject to identify the target, reflecting reaction speed; the results analysis and report writing after indicator generation are presented in various forms, including charts and bar graphs to display indicators such as average fixation time and number of fixations under different tasks; line graphs to show the trend of reaction time changes under different tasks; and heatmaps to display the distribution of fixations and analyze visual search hotspot areas under different tasks.

10. The method for simulating and evaluating motion visual ability based on the characteristics of skeet shooting as described in claim 9, characterized in that, In S4, the statistical table can summarize the statistical results and list the statistical results of each indicator, including the mean and standard deviation. The report should explain the analysis results in detail, discuss the discovered visual search patterns and their significance, and propose suggestions for further research.

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