Ice and snow sports training process control method and system based on visual information processing

Abstract

The invention discloses an ice and snow sports training process control method based on visual information processing. The ice and snow sports training process control method comprises the following steps that real-time data information of an athlete in the sports process is collected; importing historical data information and standard parameter information; judging whether the take-off position and the flight size of the athlete are qualified or not; analyzing the control action of the athlete in the skiing process so as to adjust the control process of the action; the method comprises the following steps: firstly, making a take-off area in a targeted manner according to historical motion data of each athlete, and monitoring take-off positions and landing positions of the athletes; the state of the athlete in the flight process is monitored in real time, whether the control process of the flight posture of the athlete is abnormal or not is judged according to the motion change conditions of the body of the athlete and the different positions of the skateboard, the athlete is reminded to make targeted adjustment and special breakthrough, accurate feedback and training suggestions are provided for coaches and the athlete, and the training efficiency is improved. And the training effect of athletes can be obviously improved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent management and control, and in particular to a method for controlling an ice and snow sports training process based on visual information processing. Background Art

[0002] Ski jumping is a winter sports competition in which athletes use their own kinetic energy to jump from a special platform, complete the flying action in the air, land on the landing slope and continue to slide for a distance. During the whole process, athletes need to slide freely from the platform hundreds of meters high and separate from the take-off area. The process is very fast and has certain risks.

[0003] During daily training, platform diving athletes often need to record their training process. In most cases, athletes are result-oriented and observe the problematic sports process to find the cause in order to improve themselves. However, due to the fast speed of the entire sports process, it is difficult for the naked eye to capture the changes in its movements, and it is difficult to accurately and comprehensively find the problems that arise in the training, which makes it difficult for athletes to break through the bottleneck and the training efficiency is low. In order to improve the training efficiency of athletes, a method for controlling the training process of ice and snow sports based on visual information processing is proposed. Summary of the invention

[0004] The technical problem to be solved by the present invention is: how to solve the problem that the existing safety protection system has a single protection type, resulting in poor protection effect and bringing certain impacts on the use of the safety protection system. A method for controlling the ice and snow sports training process based on visual information processing is provided.

[0005] The present invention solves the above technical problems through the following technical solutions, and the present invention comprises the following steps:

[0006] S1. Collect real-time data information of athletes during exercise;

[0007] S2, importing and storing historical data information and standard parameter information of athletes during exercise;

[0008] S3, reading the historical data information and standard parameter information of the athlete's movement process, analyzing the real-time data information in combination with the historical data information and the standard parameter information, judging whether the athlete's take-off position and flight size are qualified, and generating an evaluation report;

[0009] S4. Obtaining the real-time data information and standard parameter information of the athlete, monitoring the entire movement process of the athlete in real time, analyzing the control action of the athlete during skiing according to the real-time data information and standard parameter information, adjusting the control process of the action, and generating a feedback report;

[0010] S5. Receive and output evaluation report and feedback report.

[0011] Preferably, the historical data information includes historical image data, historical time point data and historical speed data, the real-time data information includes real-time image data and real-time size data, and the specific generation process of the evaluation report is:

[0012] Read historical video data of athletes;

[0013] Then read the standard parameter information of the athlete's daily training to obtain the athlete's take-off action data;

[0014] Acquire the first historical time point t1 of the athlete's take-off in the historical image data according to the take-off action data;

[0015] Then obtain the second historical time point t2 in the historical image data when the athlete separates from the take-off end of the diving platform;

[0016] Using the formula △ t=t2-t1 calculates the first type of time period;

[0017] Collect multiple historical speed data of the athlete when leaving the diving platform, and calculate the average departure speed V1;

[0018] Calculate the first type of skating distance of the athlete in the first type of time period using the formula L1=V1·Δt;

[0019] Collect real-time image data of the diving platform, and create a first type of virtual straight line on the diving platform, wherein the first type of virtual straight line is perpendicular to the sliding direction of the athlete, and the distance between the first type of virtual straight line and the sideline of the take-off end of the diving platform is L1;

[0020] Marking the area of ​​the diving platform between the first type of virtual straight line and the sideline of the take-off end of the diving platform to produce a take-off area A;

[0021] Collect the real-time image of point K of the diving platform, mark point K, and obtain the horizontal dimension L2 from point K to the take-off end of the diving platform;

[0022] Collect real-time video data of athletes' skating;

[0023] Import the take-off action data and obtain the athlete's take-off point;

[0024] Collect the dimension data L3 of the take-off point from the take-off end edge line of the diving platform;

[0025] Then, the landing point where the athlete touches the diving platform again after taking off is obtained based on the real-time image data;

[0026] Collect the horizontal dimension L4 of the landing point from the take-off end of the diving platform;

[0027] When L3>L1 or L4<L2, it indicates that the athlete's movement state is abnormal, and a first type of evaluation report is generated.

[0028] Preferably, the real-time data information also includes real-time speed data, and the generation process of the evaluation report also includes:

[0029] Obtain real-time image data of the jump platform;

[0030] Use the first rule to select the reference point;

[0031] The first rule is:

[0032] A second type of virtual straight line perpendicular to the sliding direction of the athlete is made on the starting end surface of the diving platform, and the midpoint B1 of the second type of straight line is obtained;

[0033] After obtaining the midpoint B2 of the sideline of the take-off end of the diving platform, connect point B1 and point B2 on the diving platform to create a virtual curve;

[0034] Select any pre-selected point B3 on the virtual curve;

[0035] Collect the vertical dimension L5 from the pre-selected point B3 to point B2;

[0036] When L5<preset threshold Q1;

[0037] Get the horizontal dimension L6 between the pre-selected points B3 and B2;

[0038] Calculate the inclination angle θ at the pre-selected point B3. The specific calculation process is:

[0039]

[0040] When the inclination angle θ is less than the preset threshold value Q2, the pre-selected point B3 is selected as the reference point;

[0041] Obtain the athlete's historical speed Ve1 at the reference point and the athlete's speed Ve2 when leaving the take-off end of the diving platform when the speed at the reference point is V2, and use the formula Le=Ve2·Δt to calculate the size Ae1 of the take-off area required by the athlete in this state;

[0042] Establish a mapping relationship between different speeds Ve of the reference point and the required size Ae of the take-off area;

[0043] Obtain the real-time speed data V2 of the athlete at the reference point;

[0044] Calculate the deviation E1 of the athlete's speed at the reference point. The specific calculation process is:

[0045]

[0046] When the deviation E1>preset threshold Q3, the size Ae2 of the take-off area required by the athlete at the reference point when the historical speed is V2 is obtained according to the mapping relationship;

[0047] Replace L1's dimensional data with Ae2's and remake the take-off area.

[0048] Preferably, the generation process of the evaluation report further includes:

[0049] Get real-time video data of athletes skating,

[0050] Import take-off action data;

[0051] Collect the size of the sideline of the athlete's take-off end from the diving platform multiple times, and obtain the average size L7;

[0052] Import the size data L1 of the take-off area A and calculate the deviation E2 of the athlete's take-off position. The specific calculation process is:

[0053]

[0054] When the deviation E2>preset threshold Q4, the size data of L7 is used to replace the size data of L1 and the take-off area is remade.

[0055] Preferably, the feedback report includes a control report and a warning report, and the specific processing process of S4 is:

[0056] Read standard parameter information and obtain the athlete's flight action data;

[0057] Collect real-time image data of athletes in flight movements;

[0058] Collect the dimension data Le1 of the distance between the athlete's geometric center and the center line of the diving platform in real time;

[0059] When Le1>preset threshold Q5, a warning report is generated;

[0060] When Le1≤preset threshold Q5, the second rule is used to obtain the verification point;

[0061] The second rule is:

[0062] Take the two skateboards as a whole to obtain the geometric center point C1 of the skateboard body, then obtain the geometric center point C2 of the athlete, and make a vertical reference virtual plane W through point C1 and point C2;

[0063] In the reference virtual plane, a virtual vertical line Lr1 is made on the top surface of the skateboard through point C1, and a virtual vertical line Lr2 is made on the top surface of the human body through point C2; the intersection of the virtual vertical line Lr1 and the virtual vertical line Lr2 is marked to obtain the verification point G;

[0064] Import standard parameter information to obtain all points to be measured during the athlete's flight process, where the points to be measured include a first point to be measured and a second point to be measured;

[0065] Collect the first type of data De and the second type of data Dr of the athlete's flight process;

[0066] The first type of data is the real-time size data De of the first to-be-measured point on the athlete's body from the verification point G;

[0067] The second type of data is collected in the following manner:

[0068] Take the second point to be measured on the skateboard, and make a virtual line in the width direction of the skateboard through the second point to be measured. The intersection points of the virtual line and the edge line of the skateboard are Ce1 and Ce2;

[0069] Measure the size data of the distance between the points Ce1 and Ce2 and the verification point respectively, and calculate the absolute value of the difference to obtain the second type of data Dr;

[0070] A first point to be measured is read arbitrarily, and X first type data are obtained continuously and in equal time periods, namely De1, De2, De3, ..., DeX;

[0071] Calculate the first dispersion E3 of the data. The specific calculation process is:

[0072]

[0073] in, is the average value of multiple first type data;

[0074] Then, a second point to be measured is read randomly, and X second type data are obtained continuously and in equal time periods, namely Dr1, Dr2, Dr3, ..., DrX;

[0075] Calculate the second dispersion E4 of the data. The specific calculation process is:

[0076]

[0077] in, is the average value of multiple second type data;

[0078] When the first dispersion E3>preset threshold Q6 or the second dispersion E4>preset threshold Q7, it indicates that the athlete has poor balance, and a first type of control report is generated.

[0079] Preferably, the generation process of the regulation report further includes:

[0080] Get all the points to be tested;

[0081] Calculate the first dispersion E3 of the first point to be measured;

[0082] When the first dispersion E3>preset threshold Q6, the first type mark is performed on the first point to be tested;

[0083] Calculate the second dispersion E4 of the second point to be measured;

[0084] When the second dispersion E4>preset threshold Q7, the second type of marking is performed on the second point to be tested;

[0085] Read the reference virtual plane W;

[0086] Count the sum M1 of the first type of marks and the second type of marks located on one side of the virtual plane W;

[0087] Then count the sum of the first type of marks and the second type of marks on the other side of the virtual plane W M2

[0088] Calculate the difference E5 of the marked points. The specific calculation process is:

[0089]

[0090] When the difference E5>preset threshold Q8, it is marked that there is a problem with the athlete's take-off angle, and a second type of regulation report is generated.

[0091] Preferably, the generation process of the regulation report further includes:

[0092] Obtain real-time image data of athletes during flight;

[0093] Real-time monitoring and detection of the first type of markers and the second type of markers on both sides of the virtual plane W respectively;

[0094] The monitoring and detection process is as follows:

[0095] Obtain the total number Me of first-type marks and second-type marks on one side of the virtual plane W every preset period;

[0096] With the total quantity Me as the ordinate and the time node as the abscissa, a rectangular coordinate graph is made to obtain a curve graph;

[0097] Randomly select two points on the curve graph, namely point N1 and point N2;

[0098] The coordinates of the reading point N1 are N1(Tu1, U1), the coordinates of the reading point N2 are N2(Tu2, U2), and Tu2>Tu1, and Tu2-Tu1>preset threshold Q9;

[0099] Calculate the slope Ku between point N1 and point N2. The specific calculation process is:

[0100] Ku=(U2-U1) / Tu2-Tu1;

[0101] When the slope Ku>0, it indicates that there is a problem with the athlete's physical fitness, and a third type of regulation report is generated.

[0102] Preferably, the generation process of the regulation report further includes:

[0103] Import the curve graph, obtain the time point Ti1 of the starting point of the curve graph and the time point Ti2 of the end point of the curve graph; when Ti2-Ti1<preset threshold Q10, it indicates that the athlete has abnormal action during the flight process, and generates the fourth type of control report.

[0104] A control system for ice and snow sports training process based on visual information processing, the control system comprising:

[0105] The data acquisition module is used to collect real-time data information of athletes during exercise;

[0106] The database module is used to import and store historical data information and standard parameter information of athletes during exercise;

[0107] The preprocessing module is used to read the historical data information and standard parameter information of the athlete's movement process, analyze the real-time data information in combination with the historical data information and the standard parameter information, determine whether the athlete's take-off position and flight size are qualified, and generate an evaluation report;

[0108] The data processing module is used to obtain the real-time data information and standard parameter information of the athletes, monitor the entire movement process of the athletes in real time, analyze the control actions of the athletes during skiing according to the real-time data information and standard parameter information, adjust the control process of the actions, and generate feedback reports;

[0109] The data output module is used to receive and output evaluation reports and feedback reports.

[0110] Compared with the prior art, the present invention has the following advantages: the method firstly creates a take-off area according to the historical sports data of each athlete, monitors the take-off position and landing position of the athlete, and preliminarily determines whether the athlete's performance meets the standard; then the state of the athlete's flight process is monitored in real time, and according to the changes in the movements of the athlete's body and different positions of the skateboard, it is determined whether there is an abnormality in the control process of the athlete's flight posture, and a judgment is made and a report is issued; the athlete is reminded to make targeted adjustments and special breakthroughs, and accurate feedback and training suggestions are provided to coaches and athletes. Through targeted movement evaluation, the training effect and competitive level of the athletes can be significantly improved; at the same time, when the flight trajectory deviates, an early warning is issued to remind the athlete to make adjustments in time, thereby improving the safety of the athlete during training, making the method more worthy of popularization and use. BRIEF DESCRIPTION OF THE DRAWINGS

[0111] Figure 1 It is the overall flow chart of the present invention. DETAILED DESCRIPTION

[0112] The following is a detailed description of an embodiment of the present invention. This embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation method and a specific operation process are given, but the protection scope of the present invention is not limited to the following embodiment.

[0113] like Figure 1 As shown, this embodiment provides a technical solution: a method for controlling the training process of ice and snow sports based on visual information processing, which is used to monitor and control the movements of ski jumping athletes during daily training, and includes the following steps:

[0114] S1. Collect real-time data information of athletes during exercise;

[0115] S2, importing and storing historical data information and standard parameter information of athletes during exercise;

[0116] It should be noted that the standard parameter information is the athlete's take-off action reference data, flying action reference data, alternate landing action reference data and athlete monitoring point distribution data pre-made according to historical data.

[0117] S3, reading the historical data information and standard parameter information of the athlete's movement process, analyzing the real-time data information in combination with the historical data information and the standard parameter information, judging whether the athlete's take-off position and flight size are qualified, and generating an evaluation report;

[0118] S4. Obtaining the real-time data information and standard parameter information of the athlete, monitoring the entire movement process of the athlete in real time, analyzing the control action of the athlete during skiing according to the real-time data information and standard parameter information, adjusting the control process of the action, and generating a feedback report;

[0119] S5. Receive and output evaluation report and feedback report.

[0120] The method first creates a take-off area based on the historical sports data of each athlete, monitors the athlete's take-off position and landing position, and preliminarily determines whether the athlete's performance meets the standard; then the athlete's flight status is monitored in real time, and based on the athlete's body and the changes in the movements of different positions of the skateboard, it is determined whether there are any abnormalities in the control process of the athlete's flight posture, and a judgment is made and a report is issued; the athlete is reminded to make targeted adjustments and special breakthroughs, and accurate feedback and training suggestions are provided to coaches and athletes. Through targeted movement evaluation, the training effect and competitive level of the athletes can be significantly improved; at the same time, when the flight trajectory deviates, an early warning is issued to remind the athlete to make timely adjustments, thereby improving the safety of the athlete during training.

[0121] Among them, historical data information includes historical image data, historical time point data and historical speed data, and real-time data information includes real-time image data and real-time size data. The specific generation process of the assessment report is as follows:

[0122] Read historical video data of athletes;

[0123] Then read the standard parameter information of the athlete's daily training to obtain the athlete's take-off action data;

[0124] Acquire the first historical time point t1 of the athlete's take-off in the historical image data according to the take-off action data;

[0125] Then obtain the second historical time point t2 in the historical image data when the athlete separates from the take-off end of the diving platform;

[0126] Using the formula △ t=t2-t1 calculates the first type of time period;

[0127] The first type of time period is the athlete’s reaction time;

[0128] Collect multiple historical speed data of the athlete when leaving the diving platform, and calculate the average departure speed V1;

[0129] Calculate the first type of skating distance of the athlete in the first type of time period using the formula L1=V1·Δt;

[0130] Collect real-time image data of the diving platform, and create a first-type virtual straight line on the diving platform. The first-type virtual straight line is perpendicular to the sliding direction of the athlete, and the distance between the first-type virtual straight line and the sideline of the take-off end of the diving platform is L1;

[0131] Marking the area of ​​the diving platform between the first type of virtual straight line and the sideline of the take-off end of the diving platform to produce a take-off area A;

[0132] Collect the real-time image of point K of the diving platform, mark point K, and obtain the horizontal dimension L2 from point K to the take-off end of the diving platform;

[0133] The K point of the diving platform is a reference line clearly marked on the diving platform, which is used to judge the flying distance of the athletes;

[0134] Collect real-time video data of athletes' skating;

[0135] Import the take-off action data and obtain the athlete's take-off point;

[0136] Collect the dimension data L3 of the take-off point from the take-off end edge line of the diving platform;

[0137] Then, the landing point where the athlete touches the diving platform again after taking off is obtained based on the real-time image data;

[0138] Collect the horizontal dimension L4 of the landing point from the take-off end of the diving platform;

[0139] When L3>L1 or L4<L2, it indicates that the athlete's movement state is abnormal, and a first type of evaluation report is generated.

[0140] This embodiment first estimates the athlete's reaction time based on each athlete's historical take-off time and time of leaving the diving platform, and then estimates the length of the athlete's take-off area based on the speed of the athlete leaving the diving platform; since the speed of the athlete when leaving the diving platform is greater than the speed during the take-off process, a safer take-off area can be divided; then the athlete's take-off position and landing position are monitored to preliminarily determine whether the athlete's performance meets the standard. By monitoring the take-off area and the take-off position, it can be determined whether the selection of the take-off timing of the moving part is appropriate, and the athlete's take-off reaction is trained in a targeted manner to improve the athlete's competitive level.

[0141] Since ski jumping is greatly affected by different venues and environments; the height and surface of the ski jumping platforms at different venues are different, and the weather also affects the wind resistance, resulting in large differences in the sliding speed of athletes on the ski jumping platforms; when the athlete's sliding speed deviation is large, it will cause a large change in the take-off area. The above embodiment only calculates the length of the take-off area by the average breakaway speed, which will result in a large error. In order to reduce the error and improve the accuracy of data monitoring during athlete training, the following further solutions are proposed:

[0142] Furthermore, the real-time data information also includes real-time speed data, and the generation process of the evaluation report also includes:

[0143] Obtain real-time image data of the jump platform;

[0144] Use the first rule to select the reference point;

[0145] The first rule is:

[0146] A second type of virtual straight line perpendicular to the sliding direction of the athlete is made on the starting end surface of the diving platform, and the midpoint B1 of the second type of straight line is obtained;

[0147] After obtaining the midpoint B2 of the sideline of the take-off end of the diving platform, connect point B1 and point B2 on the diving platform to create a virtual curve;

[0148] Select any pre-selected point B3 on the virtual curve;

[0149] Collect the vertical dimension L5 from the pre-selected point B3 to point B2;

[0150] When L5<preset threshold Q1;

[0151] Get the horizontal dimension L6 between the pre-selected points B3 and B2;

[0152] Calculate the inclination angle θ at the pre-selected point B3. The specific calculation process is:

[0153]

[0154] When the inclination angle θ is less than the preset threshold value Q2, the pre-selected point B3 is selected as the reference point;

[0155] Obtain the athlete's historical speed Ve1 at the reference point and the athlete's speed Ve2 when leaving the take-off end of the diving platform when the speed at the reference point is V2, and use the formula Le=Ve2·Δt to calculate the size Ae1 of the take-off area required by the athlete in this state;

[0156] Establish a mapping relationship between different speeds Ve of the reference point and the required size Ae of the take-off area;

[0157] Obtain the real-time speed data V2 of the athlete at the reference point;

[0158] Calculate the deviation E1 of the athlete's speed at the reference point. The specific calculation process is:

[0159]

[0160] When the deviation E1>preset threshold Q3, the size Ae2 of the take-off area required by the athlete at the reference point when the historical speed is V2 is obtained according to the mapping relationship;

[0161] Replace L1's dimensional data with Ae2's and remake the take-off area.

[0162] In this embodiment, a reference point is first established, and the speed of the athlete leaving the take-off end of the diving platform is estimated based on the speed of the reference point; since the inclination of the sliding end of the diving platform is gradually reduced, the acceleration it provides also decreases accordingly; two conditions are considered in the process of establishing the reference point, one is the vertical size of the reference point and the take-off end of the diving platform, and the other is the inclination of the reference point; when both conditions are met, it indicates that the athlete's acceleration process is basically completed, and the speed of the athlete at this time can largely represent the speed of the athlete leaving the diving platform; and the reference point has a certain reaction distance from the edge of the diving platform, which is convenient for the athlete to make timely adjustments, and the athlete's control over speed and distance can be improved; when this embodiment is specifically implemented, a mapping relationship between the speed at the reference point and the size of the take-off area is established based on historical data, and then the real-time speed of the reference point is monitored. When there is a large difference between the real-time speed and the average separation speed, timely adjustments are made to improve the athlete's take-off quality, while preventing safety accidents caused by athletes missing the take-off opportunity, thereby improving the safety of athletes during training.

[0163] Furthermore, the evaluation report generation process also includes:

[0164] Get real-time video data of athletes skating,

[0165] Import take-off action data;

[0166] Collect the size of the sideline of the athlete's take-off end from the diving platform multiple times, and obtain the average size L7;

[0167] Import the size data L1 of the take-off area A and calculate the deviation E2 of the athlete's take-off position. The specific calculation process is:

[0168]

[0169] When the deviation E2>preset threshold Q4, the size data of L7 is used to replace the size data of L1 and the take-off area is remade.

[0170] The size of the athlete's actual take-off distance from the sideline of the take-off end of the diving platform is monitored. When the actual monitored size is most likely within the take-off area and closer to the sideline of the take-off end of the diving platform, it indicates that the athlete's take-off reaction is improved and the required take-off distance is shortened. The take-off area is adaptively adjusted to ensure training intensity and improve training results.

[0171] Among them, the feedback report includes the control report and the warning report. The specific processing process of S4 is as follows:

[0172] Read standard parameter information and obtain the athlete's flight action data;

[0173] Collect real-time image data of athletes in flight movements;

[0174] Collect the dimension data Le1 of the distance between the athlete's geometric center and the center line of the diving platform in real time;

[0175] When Le1>preset threshold Q5, a warning report is generated;

[0176] When Le1≤preset threshold Q5, the second rule is used to obtain the verification point;

[0177] The second rule is:

[0178] Take the two skateboards as a whole to obtain the geometric center point C1 of the skateboard body, then obtain the geometric center point C2 of the athlete, and make a vertical reference virtual plane W through point C1 and point C2;

[0179] In the reference virtual plane, a virtual vertical line Lr1 is made on the top surface of the skateboard through point C1, and a virtual vertical line Lr2 is made on the top surface of the human body through point C2; the intersection of the virtual vertical line Lr1 and the virtual vertical line Lr2 is marked to obtain the verification point G;

[0180] Import standard parameter information to obtain all points to be measured during the athlete's flight process, where the points to be measured include a first point to be measured and a second point to be measured;

[0181] Collect the first type of data De and the second type of data Dr of the athlete's flight process;

[0182] The first type of data is the real-time size data De of the first to-be-measured point on the athlete's body from the verification point G;

[0183] The second type of data is collected in the following ways:

[0184] Take the second point to be measured on the skateboard, and make a virtual line in the width direction of the skateboard through the second point to be measured. The intersection points of the virtual line and the edge line of the skateboard are Ce1 and Ce2;

[0185] Measure the size data of the distance between the points Ce1 and Ce2 and the verification point respectively, and calculate the absolute value of the difference to obtain the second type of data Dr;

[0186] A first point to be measured is read arbitrarily, and X first type data are obtained continuously and in equal time periods, namely De1, De2, De3, ..., DeX;

[0187] Calculate the first dispersion E3 of the data. The specific calculation process is:

[0188]

[0189] in, is the average value of multiple first type data;

[0190] Then, a second point to be measured is read randomly, and X second type data are obtained continuously and in equal time periods, namely Dr1, Dr2, Dr3, ..., DrX;

[0191] Calculate the second dispersion E4 of the data. The specific calculation process is:

[0192]

[0193] in, is the average value of multiple second type data;

[0194] When the first dispersion E3>preset threshold Q6 or the second dispersion E4>preset threshold Q7, it indicates that the athlete has poor balance, and a first type of control report is generated.

[0195] When this technical solution is implemented, the distance between the athlete and the center line of the platform is first collected; when the distance deviation is large, a warning is issued to reduce safety hazards and improve skating performance; when the distance deviation is within a reasonable range, verification points are first established, and the dimensions of the athlete's body and the points to be tested on the skateboard from the verification points are collected, and the abnormality of the control action during flight is judged by calculating the fluctuation of each point; when the data is unstable, it means that the athlete's balance is poor, a report is issued, and the athlete is advised to do special balance training to improve the athlete's competitive ability in a targeted manner.

[0196] Furthermore, the generation process of the control report also includes:

[0197] Get all the points to be tested;

[0198] Calculate the first dispersion E3 of the first point to be measured;

[0199] When the first dispersion E3>preset threshold Q6, the first type mark is performed on the first point to be tested;

[0200] Calculate the second dispersion E4 of the second point to be measured;

[0201] When the second dispersion E4>preset threshold Q7, the second type of marking is performed on the second point to be tested;

[0202] Read the reference virtual plane W;

[0203] Count the sum M1 of the first type of marks and the second type of marks located on one side of the virtual plane W;

[0204] Then count the sum of the first type of marks and the second type of marks on the other side of the virtual plane W M2

[0205] Calculate the difference E5 of the marked points. The specific calculation process is:

[0206]

[0207] When the difference E5>preset threshold Q8, it is marked that there is a problem with the athlete's take-off angle, and a second type of regulation report is generated.

[0208] In this further scheme, the marked points are abnormal points. The positions of the abnormal points of the athletes are counted and the distribution of the abnormal points is analyzed. When the number of abnormal points on both sides of the athlete is obviously unbalanced, it indicates that the athlete is obviously adjusting the flight direction to control the flight trajectory during the flight. It is judged that there are deviations in the athlete's take-off action, and a targeted report is issued to remind the athlete to make improvements and improve the effectiveness of training.

[0209] Ski jumping is a long process. Unlike other ice and snow sports, it does not require varied movements and graceful postures. During competitions and training, it is often necessary to maintain a certain movement for a long time. Due to the large amount of daily training, athletes are prone to muscle fatigue, and are more likely to have abnormal movements at the rear end of the flight, which in turn causes trajectory deviation and requires adjustment of one side for correction. At this time, there is also an obvious imbalance in the number of abnormal points on both sides of the athlete, but it is not caused by problems with the take-off angle, which can easily lead to misjudgment. In order to improve the accuracy of judgment, the following further technical solutions are proposed:

[0210] Furthermore, the generation process of the control report also includes:

[0211] Obtain real-time image data of athletes during flight;

[0212] Real-time monitoring and detection of the first type of markers and the second type of markers on both sides of the virtual plane W respectively;

[0213] The monitoring and detection process is:

[0214] Obtain the total number Me of first-type marks and second-type marks on one side of the virtual plane W every preset period;

[0215] With the total quantity Me as the ordinate and the time node as the abscissa, a rectangular coordinate graph is made to obtain a curve graph;

[0216] Randomly select two points on the curve graph, namely point N1 and point N2;

[0217] The coordinates of the reading point N1 are N1(Tu1, U1), the coordinates of the reading point N2 are N2(Tu2, U2), and Tu2>Tu1, and Tu2-Tu1>preset threshold Q9;

[0218] Calculate the slope Ku between point N1 and point N2. The specific calculation process is:

[0219] Ku=(U2-U1) / Tu2-Tu1;

[0220] When the slope Ku>0, it indicates that there is a problem with the athlete's physical fitness, and a third type of regulation report is generated.

[0221] In this technical solution, the marking points on both sides of the athlete are monitored and counted respectively, and a curve graph showing the change of the number of marking points over time is produced; when the number of marking points increases over time, it indicates that there is no problem with the athlete's take-off process, and the uneven distribution of marking points on both sides is caused by abnormal movements during flight, which is caused by insufficient physical fitness of the athlete, and is reflected in the curve graph as an overall positive slope; when the number of marking points decreases over time, it indicates that there is a problem with the athlete's take-off process, and the movement of one side of the body needs to be adjusted in the early stage to adjust the trajectory, thus causing an uneven distribution of marking points on both sides. When the trajectory is adjusted to a normal position, the number of marking points decreases, and is reflected in the curve graph as an overall negative slope; a comprehensive analysis is conducted based on the actual situation to reduce the probability of misjudgment and improve the judgment accuracy of data analysis.

[0222] It should be noted that the marked points are abnormal points, which are points to be tested with problems;

[0223] Furthermore, the generation process of the control report also includes:

[0224] Import the curve graph, obtain the time point Ti1 of the starting point of the curve graph and the time point Ti2 of the end point of the curve graph; when Ti2-Ti1<preset threshold Q10, it indicates that the athlete has abnormal action during the flight process, and generates the fourth type of control report.

[0225] When the marked points on the curve graph are concentrated in a shorter period of time, it means that the athlete's overall movement posture is good and the level is high; but there are abnormal movements during the flight, which need to be paid attention to and improved and improved.

[0226] A control system for ice and snow sports training process based on visual information processing, the control system includes:

[0227] The data acquisition module is used to collect real-time data information of athletes during exercise;

[0228] The database module is used to import and store historical data information and standard parameter information of athletes during exercise;

[0229] The preprocessing module is used to read the historical data information and standard parameter information of the athlete's movement process, analyze the real-time data information in combination with the historical data information and the standard parameter information, determine whether the athlete's take-off position and flight size are qualified, and generate an evaluation report;

[0230] The data processing module is used to obtain the real-time data information and standard parameter information of the athletes, monitor the entire movement process of the athletes in real time, analyze the control actions of the athletes during skiing according to the real-time data information and standard parameter information, adjust the control process of the actions, and generate feedback reports;

[0231] The data output module is used to receive and output evaluation reports and feedback reports.

[0232] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A method for controlling the training process of ice and snow sports based on visual information processing, which is used to monitor and control the movements of ski jumping athletes during daily training, and is characterized in that: The following steps are involved: S1. Collect real-time data information of athletes during exercise; S2, importing and storing historical data information and standard parameter information of athletes during exercise; S3, reading the historical data information and standard parameter information of the athlete's movement process, analyzing the real-time data information in combination with the historical data information and the standard parameter information, judging whether the athlete's take-off position and flight size are qualified, and generating an evaluation report; S4. Obtaining the real-time data information and standard parameter information of the athlete, monitoring the entire movement process of the athlete in real time, analyzing the control action of the athlete during skiing according to the real-time data information and standard parameter information, adjusting the control process of the action, and generating a feedback report; S5. Receive and output evaluation report and feedback report.

2. The method for controlling the ice and snow sports training process based on visual information processing according to claim 1 is characterized in that: The historical data information includes historical image data, historical time point data and historical speed data, and the real-time data information includes real-time image data and real-time size data. The specific generation process of the evaluation report is as follows: Read historical video data of athletes; Then read the standard parameter information of the athlete's daily training to obtain the athlete's take-off action data; Acquire the first historical time point t1 of the athlete's take-off in the historical image data according to the take-off action data; Then obtain the second historical time point t2 in the historical image data when the athlete separates from the take-off end of the diving platform; Using the formula △ t=t2-t1 calculates the first type of time period; Collect multiple historical speed data of the athlete when leaving the diving platform, and calculate the average departure speed V1; Calculate the first type of skating distance of the athlete in the first type of time period using the formula L1=V1·Δt; Collect real-time image data of the diving platform, and create a first type of virtual straight line on the diving platform, wherein the first type of virtual straight line is perpendicular to the sliding direction of the athlete, and the distance between the first type of virtual straight line and the sideline of the take-off end of the diving platform is L1; Marking the area of ​​the diving platform between the first type of virtual straight line and the sideline of the take-off end of the diving platform to produce a take-off area A; Collect the real-time image of point K of the diving platform, mark point K, and obtain the horizontal dimension L2 from point K to the take-off end of the diving platform; Collect real-time video data of athletes' skating; Import the take-off action data and obtain the athlete's take-off point; Collect the dimension data L3 of the take-off point from the take-off end edge line of the diving platform; Then, the landing point where the athlete touches the diving platform again after taking off is obtained based on the real-time image data; Collect the horizontal dimension L4 of the landing point from the take-off end of the diving platform; When L3>L1 or L4<L2, it indicates that the athlete's movement state is abnormal, and a first type of evaluation report is generated.

3. The method for controlling the ice and snow sports training process based on visual information processing according to claim 2 is characterized in that: The real-time data information also includes real-time speed data, and the generation process of the evaluation report also includes: Obtain real-time image data of the jump platform; Use the first rule to select the reference point; The first rule is: A second type of virtual straight line perpendicular to the sliding direction of the athlete is made on the starting end surface of the diving platform, and the midpoint B1 of the second type of straight line is obtained; After obtaining the midpoint B2 of the sideline of the take-off end of the diving platform, connect point B1 and point B2 on the diving platform to create a virtual curve; Select any pre-selected point B3 on the virtual curve; Collect the vertical dimension L5 from the pre-selected point B3 to point B2; When L5<preset threshold Q1; Get the horizontal dimension L6 between the pre-selected points B3 and B2; Calculate the inclination angle θ at the pre-selected point B3. The specific calculation process is: When the inclination angle θ is less than the preset threshold value Q2, the pre-selected point B3 is selected as the reference point; Obtain the athlete's historical speed Ve1 at the reference point and the athlete's speed Ve2 when leaving the take-off end of the diving platform when the speed at the reference point is V2, and use the formula Le=Ve2·Δt to calculate the size Ae1 of the take-off area required by the athlete in this state; Establish a mapping relationship between different speeds Ve of the reference point and the required size Ae of the take-off area; Obtain the real-time speed data V2 of the athlete at the reference point; Calculate the deviation E1 of the athlete's speed at the reference point. The specific calculation process is: When the deviation E1>preset threshold Q3, the size Ae2 of the take-off area required by the athlete at the reference point when the historical speed is V2 is obtained according to the mapping relationship; Replace L1's dimensional data with Ae2's and remake the take-off area.

4. A method for controlling an ice and snow sports training process based on visual information processing according to claim 2 or 3, characterized in that: The generation process of the evaluation report also includes: Get real-time video data of athletes skating, Import take-off action data; Collect the size of the sideline of the athlete's take-off end from the diving platform multiple times, and obtain the average size L7; Import the size data L1 of the take-off area A and calculate the deviation E2 of the athlete's take-off position. The specific calculation process is: When the deviation E2>preset threshold Q4, the size data of L7 is used to replace the size data of L1 and the take-off area is remade.

5. The method for controlling the ice and snow sports training process based on visual information processing according to claim 2 is characterized in that: The feedback report includes a control report and a warning report. The specific processing process of S4 is as follows: Read standard parameter information and obtain the athlete's flight action data; Collect real-time image data of athletes in flight movements; Collect the dimension data Le1 of the distance between the athlete's geometric center and the center line of the diving platform in real time; When Le1>preset threshold Q5, a warning report is generated; When Le1≤preset threshold Q5, the second rule is used to obtain the verification point; The second rule is: Take the two skateboards as a whole to obtain the geometric center point C1 of the skateboard body, then obtain the geometric center point C2 of the athlete, and make a vertical reference virtual plane W through point C1 and point C2; In the reference virtual plane, a virtual vertical line Lr1 is made on the top surface of the skateboard through point C1, and a virtual vertical line Lr2 is made on the top surface of the human body through point C2; the intersection of the virtual vertical line Lr1 and the virtual vertical line Lr2 is marked to obtain the verification point G; Import standard parameter information to obtain all points to be measured during the athlete's flight process, where the points to be measured include a first point to be measured and a second point to be measured; Collect the first type of data De and the second type of data Dr of the athlete's flight process; The first type of data is the real-time size data De of the first to-be-measured point on the athlete's body from the verification point G; The second type of data is collected in the following manner: Take the second point to be measured on the skateboard, and make a virtual line in the width direction of the skateboard through the second point to be measured. The intersection points of the virtual line and the edge line of the skateboard are Ce1 and Ce2; Measure the size data of the distance between the points Ce1 and Ce2 and the verification point respectively, and calculate the absolute value of the difference to obtain the second type of data Dr; A first point to be measured is read arbitrarily, and X first type data are obtained continuously and in equal time periods, namely De1, De2, De3, ..., DeX; Calculate the first dispersion E3 of the data. The specific calculation process is: in, is the average value of multiple first type data; Then, a second point to be measured is read randomly, and X second type data are obtained continuously and in equal time periods, namely Dr1, Dr2, Dr3, ..., DrX; Calculate the second dispersion E4 of the data. The specific calculation process is: in, is the average value of multiple second type data; When the first dispersion E3>preset threshold Q6 or the second dispersion E4>preset threshold Q7, it indicates that the athlete has poor balance, and a first type of control report is generated.

6. The method for controlling the ice and snow sports training process based on visual information processing according to claim 5 is characterized in that: The generation process of the control report also includes: Get all the points to be tested; Calculate the first dispersion E3 of the first point to be measured; When the first dispersion E3>preset threshold Q6, the first type mark is performed on the first point to be tested; Calculate the second dispersion E4 of the second point to be measured; When the second dispersion E4>preset threshold Q7, the second type of marking is performed on the second point to be tested; Read the reference virtual plane W; Count the sum M1 of the first type of marks and the second type of marks located on one side of the virtual plane W; Then count the sum of the first type of marks and the second type of marks on the other side of the virtual plane W M2 Calculate the difference E5 of the marked points. The specific calculation process is: When the difference E5>preset threshold Q8, it is marked that there is a problem with the athlete's take-off angle, and a second type of regulation report is generated.

7. The method for controlling the ice and snow sports training process based on visual information processing according to claim 6 is characterized in that: The generation process of the control report also includes: Obtain real-time image data of athletes during flight; Real-time monitoring and detection of the first type of markers and the second type of markers on both sides of the virtual plane W respectively; The monitoring and detection process is as follows: Obtain the total number Me of first-type marks and second-type marks on one side of the virtual plane W every preset period; With the total quantity Me as the ordinate and the time node as the abscissa, a rectangular coordinate graph is made to obtain a curve graph; Randomly select two points on the curve graph, namely point N1 and point N2; The coordinates of the reading point N1 are N1(Tu1, U1), the coordinates of the reading point N2 are N2(Tu2, U2), and Tu2>Tu1, and Tu2-Tu1>preset threshold Q9; Calculate the slope Ku between point N1 and point N2. The specific calculation process is: Ku=(U2-U1) / Tu2-Tu1; When the slope Ku>0, it indicates that there is a problem with the athlete's physical fitness, and a third type of regulation report is generated.

8. The method for controlling the ice and snow sports training process based on visual information processing according to claim 7 is characterized in that: The generation process of the control report also includes: Import the curve graph, obtain the time point Ti1 of the starting point of the curve graph and the time point Ti2 of the end point of the curve graph; when Ti2-Ti1<preset threshold Q10, it indicates that the athlete has abnormal action during the flight process, and generates the fourth type of control report.

9. A control system for ice and snow sports training process based on visual information processing, characterized in that: The control system comprises: The data acquisition module is used to collect real-time data information of athletes during exercise; The database module is used to import and store historical data information and standard parameter information of athletes during exercise; The preprocessing module is used to read the historical data information and standard parameter information of the athlete's movement process, analyze the real-time data information in combination with the historical data information and the standard parameter information, determine whether the athlete's take-off position and flight size are qualified, and generate an evaluation report; The data processing module is used to obtain the real-time data information and standard parameter information of the athletes, monitor the entire movement process of the athletes in real time, analyze the control actions of the athletes during skiing according to the real-time data information and standard parameter information, adjust the control process of the actions, and generate feedback reports; The data output module is used to receive and output evaluation reports and feedback reports.

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