Multifunctional programmable visual terminal system supporting custom scene configuration

Abstract

The invention discloses a multifunctional programmable visual terminal system supporting user-defined scene configuration, which relates to the technical field of vision and comprises a scene configuration module, an image acquisition module and an image analysis module, the scene configuration module configures image acquisition parameters and image analysis parameters of a target person in a corresponding scene according to different scene use conditions, and the image acquisition module respectively selects corresponding acquisition positions in different use scenes to acquire image data of the target person; according to the system, different motion scenes are configured by utilizing customizable scene configuration, so that scene switching is carried out when the system needs to be used so as to adapt to constantly changing service requirements, higher ductility is achieved, the action mode of each motion is analyzed by utilizing vision, and the motion mode of each motion is more accurate. Action techniques are analyzed in an atomization mode, millisecond-level time sequence differences in a force generation chain are quantified, and therefore targeted training improvement is conducted on each athlete.

Description

Technical Field

[0001] The present invention relates to the field of vision technology, and specifically to a multi-functional programmable vision terminal system that supports custom scene configuration. Background Art

[0002] With the continuous development of technology, computer vision technology has been increasingly widely applied in the field of sports training and analysis. The traditional assessment of sports performance and analysis of movement techniques highly rely on the empirical judgment and naked-eye observation of coaches. This method has many limitations: First, it is difficult for the human eye to accurately capture and quantify the millisecond-level timing differences in the force application chains of various body parts during high-speed movement, such as the coordination efficiency of key links like kicking, swinging the arm, and rotating the body. Second, it is difficult for the subjective experience of coaches to form a standardized and replicable assessment system, resulting in the lack of accurate data support for training suggestions. Third, for different sports events (such as shooting and tennis dominated by the upper limbs and sprinting and high jump dominated by the lower limbs), their movement patterns, force application frameworks, and assessment criteria vary greatly. Existing vision analysis systems often lack sufficient flexibility and configurability and are difficult to quickly adapt to diverse training scenarios and changing business requirements. Although there are some motion capture and analysis systems on the market, they generally have problems such as poor scalability, weak scene adaptability, single analysis dimension (such as only focusing on the result or only on some links), and difficulty in "atomizing" the analysis and quantitative modeling of complex movements. Summary of the Invention

[0003] The purpose of the present invention is to provide a multi-functional programmable vision terminal system that supports custom scene configuration, which can support custom scene configuration, has high flexibility and extensibility, and can deeply analyze the movement technique chain, quantify millisecond-level timing differences, and eliminate the interference of congenital conditions. The programmable vision terminal system can realize the transformation of sports training from empiricism to dataization and precision, and provide a powerful tool for personalized training and scientific talent selection, so as to solve the problems raised in the above background art.

[0004] To achieve the above purpose, the present invention provides the following technical solution: A multi-functional programmable vision terminal system that supports custom scene configuration, including a scene configuration module, an image acquisition module, and an image analysis module. The scene configuration module configures the image acquisition parameters and image analysis parameters of the target person in the corresponding scene according to different scene usage situations. The image acquisition module respectively selects corresponding acquisition positions to collect image data of the target person in different usage scenes. The image analysis module performs feature factor analysis on the collected image data. The method of feature factor analysis includes the following steps: S1: Disassemble the collected image data, including the starting image data and the result image data during the process of the target person completing the action, and extract the direct characteristic factors of the target person completing the action in this scenario; S2: Project the extracted direct characteristic factors into the regional coordinate system in the corresponding scenario, and at the same time introduce the body data parameters of the target person for correction to construct the ability characteristic area of the target person completing the action; S3: Compare the result image data of the target person completing the action with the set standard result reference data, output the difference characteristic area, and bind the difference characteristic area of the target person to the ability characteristic area and output it to the display terminal.

[0005] Preferably, the scenario configuration module includes a preset motion type classification scenario library. In the motion type classification scenario library, the motion scenarios are divided into upper limb-dominated motion scenarios and lower limb-dominated motion scenarios. In the upper limb-dominated motion scenario, the image acquisition parameters focus on the arm force application framework, and in the lower limb-dominated motion scenario, the image acquisition parameters focus on the leg force application framework.

[0006] Preferably, the image acquisition module locks the starting frame of the action force application of the target person as the starting image data, and locks the key frame of the action completion state as the result image data.

[0007] Preferably, the direct characteristic factors include the first main factor, the second main factor and the third main factor. The first main factor is the dominant force application part, the second main factor is the secondary dominant force application part, and the third main factor is the end execution part.

[0008] Preferably, the construction method of the ability characteristic area in S2 includes the following steps: The proximal ends of the first main factor and the second main factor projected into the regional coordinate system in the corresponding scenario are extended and intersected with each other, and the connection line of the end points of the far ends forms a performance triangle. The included angle between the third main factor and the second main factor is used as a reference adjustment angle to judge whether the action chain timing is abnormal when completing the action.

[0009] Preferably, the method of introducing the body data parameters of the target person for correction in S2 includes: obtaining the height data m of the target person in meters, and scaling the ability characteristic area constructed by the target person by m times to balance the influence brought by the height difference.

[0010] Preferably, the standard result reference data includes standard action image data and standard spatial coordinate image data.

[0011] Preferably, the method for generating the differential feature region includes projecting the standard action image data and the result image data of the target person completing the action onto the regional coordinate system in the corresponding scene to construct a standard feature region, and the remaining region after removing the overlapping region between the two forms the differential feature region.

[0012] Preferably, the method for generating the differential feature region further includes extracting the actual terminal coordinates of the moving projectile in the result image data of the target person completing the action, connecting the standard space coordinates and the actual terminal coordinates in the regional coordinate system, and forming a spatial offset vector as the differential feature region.

[0013] Preferably, the fluctuation range of the reference adjustment angle α is associated with the risk of sports injury, and an alarm is triggered when the reference adjustment angle α deviates from the standard value by 15% continuously for 3 times.

[0014] In summary, the beneficial effects of the present invention are as follows: The present invention uses customizable scene configurations to configure different sports scenes, so as to perform scene switching when needed to adapt to changing business requirements, and has stronger extensibility. It uses visual analysis to analyze the action patterns of each sport, and atomizes the analysis of action techniques. Traditional athlete coaches rely too much on visual observation, unable to quantify the millisecond-level time sequence difference in the force application chain, and cannot conduct targeted training improvement for each athlete. Moreover, for some athletes with innate advantages, their innate advantages are likely to cover up their own abilities, resulting in an increased probability of mistakes due to the lack of corresponding matching of their own abilities. Through perspective analysis, the self-abilities of each athlete can be effectively understood, so as to conduct special development training, and at the same time, some excellent athletes can be selected; By modeling the performance triangle and transforming the force application framework into a more obvious geometric structure, the transformation from empiricism to digitization in sports training is realized, and the training efficiency of athletes is greatly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0016] Figure 1 It is a schematic diagram of the overall process framework structure of the multi-functional programmable visual terminal system supporting customizable scene configuration according to the present invention; Figure 2 It is a schematic diagram of the image acquisition process in the multi-functional programmable visual terminal system supporting customizable scene configuration according to the present invention; Figure 3 Schematic diagram of the image analysis process in the multi-functional programmable vision terminal system supporting custom scenario configuration of the present invention; Figure 4 Schematic diagram of the force application framework analysis during the high jump takeoff in the multi-functional programmable vision terminal system supporting custom scenario configuration of the present invention; Figure 5 Schematic diagram of the force application framework analysis during shooting in the multi-functional programmable vision terminal system supporting custom scenario configuration of the present invention; Figure 6 Schematic diagram of the differential feature region during the high jump in the multi-functional programmable vision terminal system supporting custom scenario configuration of the present invention. Detailed implementation manners

[0017] Now, the present invention will be further described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of the present invention. These drawings are all simplified schematic diagrams, only illustrating the basic structure of the present invention in a schematic manner, so they only show the components related to the present invention.

[0018] To facilitate the understanding of the present invention, the present invention will be described more comprehensively with reference to the relevant accompanying drawings. Several embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0019] All features disclosed in this specification, or all steps in the disclosed methods or processes, except for mutually exclusive features and / or steps, can be combined in any way.

[0020] Any feature disclosed in this specification (including any additional claims, abstract, and drawings), unless specifically stated, can be replaced by other equivalent or similar-purpose alternative features. That is, unless specifically stated, each feature is only an example of a series of equivalent or similar features.

[0021] In the present invention, unless otherwise clearly defined and limited, terms such as "installation", "connection", "linkage", "fixation", etc. shall be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral one; it can be a mechanical connection, a direct connection, or an indirect connection through an intermediate medium, and it can be the communication inside at least two elements or the interaction relationship between at least two elements, unless otherwise clearly defined. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0022] Please refer to Figures 1-6 , an embodiment provided by the present invention: A multi-functional programmable vision terminal system that supports custom scene configuration is used to analyze the athletic abilities of various athletes, so as to help athletes improve their performance, including sprinting, high jump, long jump, shooting, tennis, etc. Specifically, the multi-functional programmable vision terminal system that supports custom scene configuration includes a scene configuration module, an image acquisition module, and an image analysis module. The scene configuration module can be custom programmed to configure corresponding sports scenes for different sports types, so as to flexibly respond to different sports needs, and configure the corresponding image acquisition parameters and image analysis parameters of the target person for different sports scenes. Because in different sports, the movements and the force application patterns of the corresponding limbs when the athlete completes the sport are different, so different image data of the target person need to be collected and different image analyses need to be performed in different sports scenes. If the sports are classified according to the force application patterns of the limbs, they can be roughly divided into two categories, namely the upper limb-dominated sports scene and the lower limb-dominated sports scene. Among them, the upper limb-dominated sports scene includes shooting, tennis, table tennis, etc., and the lower limb-dominated sports scene includes sprinting, high jump, long jump, etc.

[0023] The image acquisition module respectively selects corresponding image acquisition positions to collect image data of the target person in different configured scenes, locks the starting frame of the action force application of the target person as the starting image data, and locks the key frame of the completed state of the action as the result image data. At the same time, the image analysis module performs associated feature analysis on the collected image data, and analyzes the image data of the athlete's movement during the process of completing this type of sport to find the best limb force application framework structure of the athlete, so as to help the athlete improve the ability to complete the action.

[0024] Specifically refer to Figure 4 , select the high jump as the background in the lower limb-dominated sports scene; The image acquisition parameters during the high jump are mainly based on the legs, and the image acquisition positions are also selected from the take-off position of the athlete when performing the high jump and the image data of the athlete's highest jump position. The image data of the athlete's take-off position is the starting image data of the target person completing the action, and the image data of the highest jump position is the result image data. The image data of the two positions are disassembled to extract multi-angle leg image data. The legs are the direct characteristic factors of the athlete completing the high jump action. The force framework of the legs when taking off is the main factor that determines the athlete's high jump height. The force framework of the entire leg is composed of the thigh, calf and foot, so the thigh is the first main factor among the direct characteristic factors, the calf is the second main factor, and the foot is the third main factor. The extracted first principal factor, second principal factor and third principal factor are projected into the regional coordinate system in the high jump scenario. If the straight line formed by the first principal factor and the straight line formed by the second principal factor do not intersect, the near ends of the two are extended to the intersection at the same time, and the straight lines at the endpoints far away are connected to form a performance triangle as the take-off ability characteristic area of the athlete completing the high jump action. The straight line formed by the third principal factor and the second principal factor will form an angle α in the coordinate system, which is set as the reference adjustment angle α. At the same time, since the height data of the athlete has an impact on the high jump movement, this part is the innate advantage, and in order to specifically analyze the ability of the athlete, it is necessary to reduce the impact of the innate advantage. Therefore, the height data parameters of the target person are introduced for correction, wherein the height data m of the target person is obtained in meters, and the ability characteristic area constructed by the target person is scaled by m times to balance the impact of the height difference, thereby constructing the take-off ability characteristic area of the athlete completing the high jump action and obtaining the reference adjustment angle α; refer to Figure 6 After obtaining the athlete's take-off ability characteristic area, the athlete's high jump result is analyzed. First, the standard result reference image data of the athlete's high jump height is retrieved. In the high jump sport, each height is equipped with reference image data corresponding to the standard result, which is used to detect whether the athlete's high jump meets the standard and whether the action is standardized. The position image data of the athlete jumping to the highest point is used for comparison between the result image data and the standard result reference image data, mainly distinguishing the difference between the distance between the back and the high jump pole and the distance between the back and the high jump pole under the standard result. The athlete's back and the high jump pole under the standard result are projected in the regional coordinate system, and the highest point and the lowest point of the athlete's back are respectively vertically connected to the high jump pole, thereby forming a characteristic area of the standard result. Similarly, an actual characteristic area is formed in the position image data of the athlete jumping to the highest point, and the actual characteristic area is overlapped with the characteristic area of the standard result. After removing the overlapping areas in the actual characteristic area, the remaining is the difference characteristic area. The athlete's difference characteristic area and the ability characteristic area are bound and output to the display end.

[0025] It should be noted that in the high jump example, high jumper A, with a height of 1.65 m, attempts to jump over a height of 1.40 m; 1. Construction of the takeoff ability characteristic region: Image acquisition: Capture the postures at the instant of takeoff and the highest point.

[0026] Extraction of main factors: Angles and positions of the thigh (first), calf (second), and foot (third).

[0027] Performance triangle: The extension lines of the thigh and calf intersect at a relatively far distance, forming a triangle with a small area, indicating insufficient force application and uncoordinated leg extension.

[0028] Reference adjustment angle α: The angle α formed by the foot and the calf is significantly small, indicating that the takeoff angle may be too low and the upward force application is insufficient.

[0029] Height correction: The triangle is scaled by 1.65 times.

[0030] Output feature: The takeoff ability characteristic region.

[0031] 2. Analysis of result differences: Standard reference: The image of successfully clearing the bar at a height of 1.40 m, with the back slightly arched and the hip passing over the bar.

[0032] Actual result image: There is still a large distance between the back of the athlete at the highest point and the bar, and the body is in a "sitting position", with obvious hip dropping.

[0033] Difference characteristic region: The overlap degree between the actual characteristic region and the standard region is low, and the area of the difference region is large, indicating that the height has not been reached and the bar - passing technique is poor.

[0034] Transmit the takeoff ability characteristic region and the difference characteristic region to the display terminal, and corresponding suggestions can be given: Insufficient takeoff force application (small triangle area), low takeoff angle (small α angle), resulting in insufficient takeoff height; The bar - passing technique needs to be greatly improved (obvious hip dropping); It is recommended to focus on strengthening leg explosive power training (such as squat jumps, box jumps) and improving the takeoff extension angle (such as marking the takeoff point for practice), and at the same time learn the basic Fosbury Flop technique.

[0035] High jumper B, with a height of 1.80 m, attempts to jump over a height of 1.80 m; 1. Construction of the takeoff ability characteristic region: Performance triangle: The extension lines of the thigh and calf intersect at a reasonable position, forming a triangle with a moderate area and a shape close to the ideal, indicating relatively sufficient and coordinated force application.

[0036] Reference adjustment angle α: The angle α formed by the foot and the calf is close to the ideal value, indicating that the takeoff angle is appropriate.

[0037] Height correction: The triangle is scaled by 1.80 times.

[0038] Output feature: Takeoff ability feature area.

[0039] 2. Result difference analysis: Standard reference: Standard over-bar image at a height of 1.80m.

[0040] Actual result image: The athlete successfully cleared the bar, but slow motion showed a slight downward pressure on the back at the moment of crossing the bar, causing the bar to shake slightly but not fall.

[0041] Difference feature area: The actual feature area coincides highly with the standard area, and the difference area is small and mainly located in the upper back, indicating sufficient height but a slight flaw in the back posture at the moment of crossing the bar.

[0042] Transmit the takeoff ability feature area and the difference feature area to the display end, so as to give corresponding suggestions: Excellent takeoff ability (ideal triangle area, good α angle); The over-bar height is sufficient, but there is a slight downward pressure on the back at the moment of crossing the bar (small difference area in the upper back), causing the bar to shake. It is recommended to focus on the refinement training of the over-bar technique, especially emphasizing maintaining the back arch posture until the hips cross the bar (such as: mental control practice at the moment of crossing the bar, using elastic bands to assist in feeling the back posture).

[0043] High jumper C, with a height of 1.92m, challenges a height of 2.30m; 1. Construction of takeoff ability feature area: Performance triangle: Large area, ideal shape, top-notch takeoff explosive power and coordination.

[0044] Reference adjustment angle α: Very close to the optimal value.

[0045] Height correction: The triangle is scaled by 1.92 times.

[0046] Output feature: Takeoff ability feature area.

[0047] 2. Result difference analysis: Standard reference: Standard over-bar image at a height of 2.30m.

[0048] Actual result image: The athlete successfully cleared the bar, but high-speed photography showed an extremely slight hook action of the calf after crossing the bar, and the bar shook violently but did not fall.

[0049] Difference feature area: The actual feature area almost coincides with the standard area. The area of the difference area is extremely small and is only located near the end of the calf / ankle, indicating that the overall pole vault is excellent, and there is only a tiny difference in the timing of calf recovery.

[0050] Transmit the takeoff ability feature area and the difference feature area to the display end, so that corresponding suggestions can be given: The takeoff ability is at the top level (large triangle, optimal α angle). The analysis shows that the pole vault action is almost perfect when successfully crossing 2.30m. There is only a millisecond-level delay (tiny difference area) in the timing of calf / ankle recovery, resulting in the pole shaking. It is recommended to strengthen the neuromuscular sense of the calf recovery timing through high-speed video playback, or consciously start the calf recovery action a few tenths of a second earlier when attempting at the limit height.

[0051] It is also worth mentioning that in this embodiment, the shooting sport is selected as the background in the upper limb-dominated motion scenario, referring to Figure 5 ; During the shooting sport, mainly the athlete throws the basketball by exerting force with the arm. Therefore, during the shooting sport, the image acquisition parameters are mainly selected based on the arm, and the image acquisition position is also selected as the image data at the shooting moment when the athlete throws the basketball and the image data when the basketball is at the basket position. The image at the shooting moment is the starting image data, and the basketball as the moving projection object at the basket position is the result image data. The image data at these two positions are disassembled to extract multi-angle arm image data. The arm is the direct feature factor for the athlete to complete the shooting action. The force application framework of the arm during shooting is the main factor determining whether the athlete can score a basket. The entire force application framework of the arm consists of the upper arm, the lower arm, and the hand. Therefore, the upper arm is the first main factor among the direct feature factors, the lower arm is the second main factor, and the hand is the third main factor. Projected in the regional coordinate system of the shooting scenario, a performance triangle is also formed as the ability feature area for the athlete to complete the shooting action. There will also be an angle α formed between the hand and the lower arm, which is set as the reference adjustment angle α. After introducing the height data parameter for correction, the ability feature area for the athlete to complete the shooting action is constructed, and at the same time, the reference adjustment angle α is obtained; Analyze the result image data of shooting, extract the standard result reference image data of the basketball entering the basket to detect the shooting result of the athlete, and compare the result image data of the athlete's shooting with the standard result reference image data. The main thing is to distinguish the distance that the center of the basketball deviates from the center of the basket after the basketball enters the basket. The standard result reference image data is that the center of the basketball is located at the center of the basket, and at this time, the center coordinates of the basketball coincide with the center coordinates of the basket. In the standard result reference image data, the actual terminal coordinates of the moving projection object are the center coordinates of the basket. At this time, there is no need to project the reference image data of the standard result, and directly project the result image data of the athlete's shooting to obtain the central projection coordinates of the basketball and the basket. The central projection coordinates of the basketball are the actual terminal coordinates of the moving projection object, and the central projection coordinates of the basket are the standard space coordinates. Connect the center point of the basketball with the center point of the basket to form a spatial offset vector as the differential feature area. The shorter the distance, the more accurate the shooting. Bind the differential feature area of the athlete to the ability feature area and output it to the display end.

[0052] It should be noted that in this embodiment, the fluctuation range of the reference adjustment angle α is associated with the risk of sports injury. First, different standard values of the reference adjustment angle α are configured according to different sports scenarios in each scenario configuration. When the reference adjustment angle α deviates from the standard value by 15% continuously for 3 times, an alarm is triggered to remind the athlete to pay attention.

[0053] Specifically, in the shooting example, take player A with a height of 1.75m and a free throw shooting percentage < 30% as an example; 1. Construction of the ability feature area: Performance triangle: The extended lines of the upper arm and the lower arm need to extend significantly and intersect to form a long and narrow obtuse triangle, indicating that the timing of the forward push of the upper arm and the extension of the lower arm is broken. Reference adjustment angle α: The angle α between the wrist and the lower arm is 15° (standard ≥ 25°), indicating that the wrist is stiff and the "wrist flick" action is not formed; Height correction: The area of the triangle is only 0.8㎡ after being scaled by 1.75 times (standard value 1.6㎡). 2. Result difference analysis: Position of the basketball entering the basket: Deviating 35cm from the center of the basket (seriously left deviation) Differential feature area: The long strip-shaped offset area points to the lower left, and combined with the ability feature area, it locks the interference of the left hand on the force. 3. Transmit to the display end, so that corresponding suggestions can be given: Disconnected force (the actions of the upper arm and the lower arm are separated) + stiff wrist + interference from the left hand resulting in serious left deviation Training instructions: ① Decompose the practice: Fixed bracket training for the upper arm (forcing the upper arm to be stable) - correct the shape of the triangle; ② Wrist weighted dribbling (increase angle α to over 25°); ③ The non - shooting hand wears a glove (reduce the pressure exerted by the left hand).

[0054] Player B, with a height of 1.88m and a three - point shooting percentage of 35% (frequently hitting the front of the basket); 1. Construction of ability characteristic area: Performance triangle: The shape is complete but the height is insufficient, where the upper - arm lifting angle is only 40° (standard 55° - 60°); Reference adjustment angle α: α = 28° (meeting the standard) but the formation timing is delayed, and it is found that the wrist - flicking action lags behind the forearm extension; Height correction: The area of the triangle is 1.4㎡ (close to the standard 1.6㎡) 2. Analysis of result differences: Basketball entry point into the basket: Deviated 12cm from the center (hitting the front of the basket on the front - right side) Difference characteristic area: Shifting forward, indicating that the shooting parabola is too low; 3. Transmit to the display terminal, so as to give corresponding suggestions: Insufficient upper - arm lifting leads to a low release angle + delayed wrist - flicking weakens the backspin of the ball; Training instructions: ① High - arc bull's - eye training: Hang a ring target 30cm above the basket (forcefully increase the parabola); ② Synchronization correction: Command training "elbow to the top - wrist exertion" (solve the delay of angle α).

[0055] To sum up, the present invention uses customizable scenario configurations to configure different sports scenarios, so as to switch scenarios when needed to adapt to changing business requirements, and has stronger extensibility. By using visual analysis of the action patterns of each sport, the action techniques are atomized and analyzed. Traditional athlete coaches rely too much on visual observation, unable to quantify the millisecond - level timing differences in the force - exerting chain, and cannot conduct targeted training improvement for each athlete. Moreover, for some athletes with innate advantages, their innate advantages are likely to cover up their own abilities, resulting in an increased probability of mistakes due to the lack of corresponding matching of their own abilities. Through visual analysis, the self - abilities of each athlete can be effectively understood, so as to conduct special development training, and at the same time, some excellent athletes can be selected; By modeling the performance triangle and transforming the force - exerting framework into a clearer geometric structure, the transformation from empiricism to digitization in sports training is realized, greatly improving the training efficiency of athletes.

[0056] The above is only a specific implementation of the invention, but the protection scope of the invention is not limited to it. Any changes or substitutions that are not conceived through creative work should be included in the protection scope of the invention. Therefore, the protection scope of the invention should be based on the protection scope defined in the claims.

Claims

1. A multi-functional programmable vision terminal system supporting custom scenario configuration, characterized in that: It includes a scene configuration module, an image acquisition module, and an image analysis module. The scene configuration module configures the image acquisition parameters and image analysis parameters of the target person in the corresponding scene according to different scene usage situations. The image acquisition module respectively selects corresponding acquisition positions to collect image data of the target person in different usage scenarios. The image analysis module analyzes the feature factors of the collected image data. The method for analyzing the feature factors includes the following steps: S1: Decompose the collected image data, including the starting image data and the result image data during the process of the target person completing the action, and extract the direct feature factors of the target person completing the action in this scene; S2: Project the extracted direct feature factors into the regional coordinate system in the corresponding scene, and at the same time introduce the body data parameters of the target person for correction to construct the ability feature area of the target person completing the action; S3: Extract the result image data of the target person completing the action and compare it with the set standard result reference data, output the difference feature area, and bind the difference feature area of the target person with the ability feature area and output it to the display end.

2. The multifunctional programmable vision terminal system supporting customized scenario configuration according to claim 1, characterized in that: The scene configuration module includes a preset motion type classification scene library. In the motion type classification scene library, the motion scenes are divided into upper limb dominant motion scenes and lower limb dominant motion scenes. In the upper limb dominant motion scenes, the image acquisition parameters focus on the arm force - generating framework, and in the lower limb dominant motion scenes, the image acquisition parameters focus on the leg force - generating framework.

3. The multi-functional programmable vision terminal system supporting customized scenario configuration according to claim 2, characterized in that: The image acquisition module locks the starting frame of the action force of the target person as the starting image data and locks the key frame of the action completion state as the result image data.

4. The multifunctional programmable vision terminal system supporting customized scenario configuration according to claim 1, characterized in that: The direct feature factors include the first main factor, the second main factor, and the third main factor. The first main factor is the dominant force - generating part, the second main factor is the secondary dominant force - generating part, and the third main factor is the end - executing part.

5. The multi-functional programmable vision terminal system supporting customized scenario configuration according to claim 4, characterized in that: The construction method of the ability feature area in S2 includes the following steps: The proximal ends of the first main factor and the second main factor projected into the regional coordinate system in the corresponding scene are extended and intersected with each other, and the connection line of the distal - end endpoints forms a performance triangle. The included angle between the third main factor and the second main factor is used as a reference adjustment angle to judge whether the action - chain time sequence is abnormal when completing the action.

6. The multifunctional programmable vision terminal system supporting custom scenario configuration according to claim 5, characterized in that: The method for introducing the body data parameters of the target person for correction in S2 includes: Obtain the height data m of the target person in meters, and scale the ability feature area constructed by the target person by m times to balance the influence brought by the height difference.

7. The multifunctional programmable vision terminal system supporting customized scenario configuration according to claim 6, characterized in that: The standard result reference data includes standard action image data and standard spatial coordinate image data.

8. The multi-functional programmable vision terminal system supporting custom scenario configuration according to claim 7, characterized in that: The generation method of the difference feature area includes projecting the standard action image data and the result image data of the target person completing the action into the regional coordinate system in the corresponding scene to construct a standard feature area, and the remaining area after removing the overlapping area between the two forms the difference feature area.

9. The multifunctional programmable vision terminal system supporting custom scenario configuration according to claim 8, characterized in that: The method for generating the differential feature region further includes extracting the actual terminal coordinates of the moving projectile in the result image data of the target person's completed action, connecting the standard space coordinates and the actual terminal coordinates in the regional coordinate system to form a spatial offset vector as the differential feature region.

10. The multifunctional programmable vision terminal system supporting custom scenario configuration according to claim 9, characterized in that: The fluctuation range of the reference adjustment angle is associated with the risk of sports injury, and a warning is triggered when the reference adjustment angle continuously deviates from the standard value.

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