Billiard training data tracking analysis system and method and billiard table thereof

Abstract

The invention discloses a billiard training data tracking analysis system and method and a billiard table thereof. According to the technical scheme provided by the invention, in the system, an acquisition module is used for acquiring a ball hitting action image of a trainee and a corresponding billiard ball running line and running initial speed; the judgment module is used for judging whether the recommended ball hitting data is met or not according to the recommended ball hitting data in combination with the ball hitting action image and the corresponding billiard ball running line and running initial speed; the statistics module is used for performing statistics on comprehensive training data of the current training according to the judgment result of each ball; and the output module is used for outputting the comprehensive training data and obtaining an overall training result of the current training in combination with the historical training data. According to the invention, based on monitoring of actions and billiard lines and speeds of the trainee, the accuracy of the trainee in multiple dimensions in the current training is accurately judged, so that the result of the current training is scientifically determined, the key point of the next training is further obtained, and the pertinence and the overall efficiency of the training are effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of sports assistance, and in particular to a billiards training data tracking and analysis system, method and billiard table. Background Art

[0002] In recent years, the research on sports science has gradually deepened. With the aim of improving sports effects and performance, various types of sports are studied, and new technologies are used to assist the training process of various sports.

[0003] Among them, the training process for various sports is based on the research on the characteristics of the sport and the selection of training methods in accordance with the different abilities required for the sport, so as to complete the specific training of the required abilities.

[0004] At present, the training method for billiards is usually still a comprehensive training method arranged by humans. This kind of training method is difficult to be targeted at the weak aspects of the trainees, and it is impossible to scientifically and accurately determine the training focus to improve the efficiency and targeting of training; in the overall training process, the degree of intelligence is also low. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a billiard training data tracking and analysis system and a corresponding billiard training data tracking and analysis method and a billiard table.

[0006] According to one aspect of the present invention, a billiards training data tracking and analysis system is provided, the system comprising: a collection module, a judgment module, a statistics module and an output module; wherein:

[0007] The acquisition module is used to obtain the trainee's hitting action image and the corresponding billiard ball running line and initial running speed based on the camera;

[0008] The judging module is used to judge whether the shot meets the recommended shot data based on the recommended shot data generated for each shot, in combination with the shot action image of the trainee and the corresponding billiard ball running line and initial running speed, and obtain a judgment result;

[0009] The statistical module is used to collect the comprehensive training data of the training session according to the judgment result of each shot;

[0010] The output module is used to output the comprehensive training data of the current training, and output the overall training results of the current training based on the historical training data of the previous training and the comprehensive training data of the current training.

[0011] In the above solution, the acquisition module is further used for:

[0012] The billiard ball running path at least includes a white ball running path and a target ball running path; the running initial speed is the white ball running initial speed;

[0013] According to the trainee's hitting action and the corresponding billiard ball running route and initial running speed.

[0014] In the above solution, the judgment module is further used to:

[0015] Determine recommended hitting data according to the hitting action image; wherein the recommended hitting data at least includes a recommended running route and a recommended initial speed;

[0016] Based on the recommended hitting data, the trainee's billiard ball running route and initial running speed are compared with the obtained recommended hitting data;

[0017] According to the comparison result, it is judged whether the training person's hitting of the ball meets the recommended hitting data, and a judgment result is obtained.

[0018] In the above solution, the judgment module is further used to:

[0019] Compare the billiard running line with the recommended running line to determine the maximum distance between the two running lines;

[0020] Determine whether the maximum spacing is greater than the preset spacing; if so, determine that the billiards running route does not conform to the recommended running route; if not, determine that the billiards running route conforms to the recommended running route;

[0021] Compare the initial running speed with the recommended initial speed to determine the maximum speed difference between the two;

[0022] Calculate the speed difference ratio between the maximum speed difference and the recommended initial speed, and determine whether the speed difference ratio is greater than a preset ratio; if so, determine that the running initial speed does not meet the recommended initial speed; if not, determine that the running initial speed meets the recommended initial speed.

[0023] In the above solution, the statistical module is further used for:

[0024] Obtain the total number of hits of the trainee during the training and the judgment result of each hit;

[0025] Based on the judgment result of each shot, the number of shots that meet the recommended running line and the number of shots that meet the recommended initial speed are calculated;

[0026] According to the calculation results, the route accuracy rate of the training that meets the recommended running route and the speed accuracy rate that meets the recommended initial speed are obtained, so as to obtain the comprehensive training data of the training.

[0027] In the above solution, the output module is further used for:

[0028] Compare the comprehensive training data of the current training with the historical training data of the previous training;

[0029] Determine the overall training results of the current training according to the training data comparison results, and output them through multimedia display;

[0030] The training focus for the next training session is determined based on the data with lower accuracy in the overall training results, and is output through multimedia display.

[0031] In the above solution, the judgment module is also used for:

[0032] Based on the acquired batting action image of the trainee, the batting action image is compared with the recommended action image;

[0033] Determine consistency parameters between the batting action image and the recommended action image;

[0034] According to the consistency parameter and the preset parameter, it is judged whether the batting action image conforms to the recommended action image, so as to provide the statistical module with statistical action accuracy.

[0035] In the above solution, the judgment module is also used for:

[0036] Decompose the batting action image and the recommended action image into an xy plane, a yz plane, and an xz plane according to each two coordinate axis planes;

[0037] The coordinates of the feature point k in the xy plane, yz plane and xz plane in the batting action image and the recommended action image are obtained respectively, and the feature point sequence on each plane is obtained; among which, the feature point sequence in the xy plane in the batting action image is The feature point sequence in the xy plane of the recommended action image is The rest of the planes can be inferred in this way;

[0038] Calculate the distance l between the corresponding feature points of the batting action image and the recommended action image on the xy plane, yz plane, and xz plane respectively

[0039]

[0040] Where n is the number of feature points on the plane; are the coordinates of the i-th feature point in the batting action image; are the coordinates of the i-th feature point in the recommended action image;

[0041] According to the distance of feature points on the xy plane, yz plane and xz plane, calculate the feature distance L of the feature point

[0042]

[0043] Among them, l i That is, the distance between the corresponding feature points on the xy plane, the yz plane, and each of the xz planes;

[0044] The feature distance L is used as a consistency parameter and combined with preset parameters to determine whether the batting action image conforms to the recommended action image.

[0045] According to another aspect of the present invention, a method for tracking and analyzing billiards training data is provided, comprising:

[0046] Based on the camera, the trainee's hitting action image and the corresponding billiard ball running line and initial running speed are obtained;

[0047] According to the recommended hitting data generated for each hitting, combined with the hitting action image of the trainee and the corresponding billiard ball running line and initial running speed, it is judged whether the hitting meets the recommended hitting data to obtain a judgment result;

[0048] According to the judgment result of each shot, the comprehensive training data of the training session is counted;

[0049] Output the comprehensive training data of the current training, and based on the historical training data of the previous training and the comprehensive training data of the current training, output the overall training results of the current training.

[0050] A billiard table is provided, the billiard table using the above-mentioned billiard training data tracking and analysis system, comprising: a table body, a guide rail and a placement mechanism; wherein:

[0051] The table body further comprises: table legs, a table top, a ball bag and a table edge; wherein the table top is rectangular;

[0052] The placing mechanism is located on one side of a short side of the rectangular desktop;

[0053] The guide rail has a downward slope, and respectively goes from the two corner pockets on the side where the placement mechanism is located, passes under the ball pockets on the long sides of each, and finally converges at the short side on the other side and connects to the placement mechanism;

[0054] Among them, after the billiard ball falls into the ball pocket, it enters the guide rail and runs along the guide rail to the placement mechanism; the placement mechanism is used to place the collected billiard balls at a preset position on the table according to a preset style after the game is over.

[0055] According to the technical solution provided by the present invention, a billiard training data tracking and analysis system includes: an acquisition module, a judgment module, a statistics module and an output module; wherein the acquisition module is used to obtain a trainee's batting action image and a corresponding billiard running line and an initial running speed based on a camera; the judgment module is used to judge whether the batting meets the recommended batting data based on the recommended batting data generated for each batting, in combination with the trainee's batting action image and the corresponding billiard running line and an initial running speed, to obtain a judgment result; the statistics module is used to count the comprehensive training data of the current training based on the judgment result of each batting; the output module is used to output the comprehensive training data of the current training, and output the overall training results of the current training based on the historical training data of the previous training and the comprehensive training data of the current training. The training process is carried out by collecting images of the trainee's batting action, the running route of the billiard ball, and the initial running speed; the recommended batting route and recommended initial running speed of the batting are scientifically determined using the batting action images; the actual running routes of the white ball and the target ball are compared with the recommended batting route; the initial running speed of the white ball is compared with the recommended initial running speed; based on the distance from the recommended route and the difference ratio with the recommended speed, it is accurately determined whether the route and batting strength of the batting are in line with the recommended batting data; and then the training is statistically analyzed to determine the batting data of the training. The accuracy of the line and the strength of the shot are used as the training data for the current training; by comparing the current training data with the historical training data, the training results of the current training are scientifically determined, clearly showing the progress of the trainee in the current training compared with the previous training, and also reflecting the aspects that still need to be improved, which are used as the key items for the next training, and the training methods suitable for the current situation of the trainee are intelligently and targetedly determined accordingly, which greatly improves the adaptability and scientificity of the training, and thus effectively improves the training effect, and also greatly improves the intelligence of billiards training. At the same time, based on the feature point sequence in the batting action image and the recommended action image, the consistency parameter is calculated to scientifically determine whether the batting action image conforms to the recommended action image, to intelligently judge the accuracy of the trainee's batting action, so as to assist the system in determining the overall action accuracy in the current training, and further select the focus of the next training, further improving the scientificity of the training.

[0056] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0057] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0059] Figure 1 A structural block diagram of a billiards training data tracking and analysis system according to an embodiment of the present invention is shown;

[0060] Figure 2 A schematic diagram showing a flow chart of a method for determining ball hitting data according to an embodiment of the present invention;

[0061] Figure 3 A schematic flow chart of a method for determining a running line according to an embodiment of the present invention is shown;

[0062] Figure 4 A schematic diagram showing a flow chart of an initial speed determination method according to an embodiment of the present invention;

[0063] Figure 5 A schematic diagram showing a flow chart of a method for counting ball hitting accuracy according to an embodiment of the present invention;

[0064] Figure 6 A schematic flow chart of a method for determining and outputting training results according to an embodiment of the present invention is shown;

[0065] Figure 7 A schematic flow chart of a method for determining the accuracy of a ball hitting action according to an embodiment of the present invention is shown;

[0066] Figure 8 A schematic flow chart of a method for tracking and analyzing billiards training data according to an embodiment of the present invention is shown;

[0067] Fig. 9 A schematic structural diagram of a billiard table according to an embodiment of the present invention is shown;

[0068] Fig.10 A schematic structural diagram of a computing device according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0069] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0070] Figure 1 The structure block diagram of a billiards training data tracking and analysis system according to an embodiment of the present invention is shown, the system comprises: a collection module 101, a judgment module 102, a statistics module 103 and an output module 104; wherein,

[0071] The acquisition module 101 is used to obtain the trainee's hitting action image and the corresponding billiard ball running line and initial running speed based on the camera.

[0072] Specifically, the billiard ball running route at least includes a white ball running route and a target ball running route; the running initial speed is the white ball running initial speed;

[0073] According to the trainee's hitting action and the corresponding billiard ball running route and initial running speed.

[0074] The judgment module 102 is used to judge whether the shot meets the recommended shot data based on the recommended shot data generated for each shot, in combination with the trainee's shot action image and the corresponding billiard ball running line and initial running speed, and obtain a judgment result.

[0075] The statistical module 103 is used to collect statistics of comprehensive training data of the current training according to the judgment result of each hitting.

[0076] The output module 104 is used to output the comprehensive training data of the current training, and output the overall training results of the current training based on the historical training data of the previous training and the comprehensive training data of the current training.

[0077] A billiards training data tracking and analysis system provided according to the present embodiment includes: an acquisition module, a judgment module, a statistics module and an output module; wherein the acquisition module is used to obtain a trainee's batting action image and a corresponding billiard ball running line and an initial running speed based on a camera; the judgment module is used to judge whether the batting meets the recommended batting data based on the recommended batting data generated for each batting, in combination with the trainee's batting action image and the corresponding billiard ball running line and an initial running speed, to obtain a judgment result; the statistics module is used to count the comprehensive training data of the current training based on the judgment result of each batting; the output module is used to output the comprehensive training data of the current training, and output the overall training results of the current training based on the historical training data of the previous training and the comprehensive training data of the current training. A billiards training data tracking and analysis system provided by the present embodiment collects images of the trainee's batting action, the billiards running route, and the initial running speed; uses the batting action images to scientifically determine the recommended batting route and recommended initial speed of the batting, compares the billiards running route with the recommended batting route, and compares the initial running speed with the recommended initial speed, to determine whether the route and batting strength of the batting meet the recommended batting data, and then performs statistics on the current training to determine the accuracy of different training contents in the current training, which is used as the training data of the current training; compares the current training data with the historical training data to scientifically determine the training results of the current training, clearly showing the trainee's progress in the current training compared with the previous training, and also reflecting the aspects that still need to be improved, which are used as the key items of the next training, and intelligently and specifically determine the training method suitable for the trainee's current situation, thereby greatly improving the adaptability and scientificity of the training, thereby effectively improving the training effect, and greatly improving the intelligence of billiards training.

[0078] Figure 2 FIG. 4 is a flow chart showing a method for determining ball hitting data according to an embodiment of the present invention. Figure 2 As shown, the method comprises the following steps:

[0079] Step S201, determining recommended batting data according to the batting action image.

[0080] Preferably, the recommended hitting data at least includes a recommended running line and a recommended initial speed.

[0081] Among them, the recommended running route in the recommended batting data is based on the analysis of the batting action image, and according to the trainee's club direction, the positional relationship between the white ball and the target ball, the recommended running route and recommended initial speed that conform to the batting action are obtained.

[0082] Step S202, based on the recommended hitting data, the trainee's billiard ball running route and initial running speed are compared with the obtained recommended hitting data.

[0083] Preferably, Figure 3 FIG. 4 is a flow chart showing a method for determining a running line according to an embodiment of the present invention. Figure 3 As shown, the method includes:

[0084] Step S301, comparing the billiard ball running route with the recommended running route to determine the maximum distance between the two running routes.

[0085] Step S302, determining whether the maximum spacing is greater than a preset spacing.

[0086] Specifically, a coordinate system is constructed with the starting point of the recommended running route (i.e., the initial position of the white ball) as the origin and the straight line connecting the starting point and the end point (i.e., the target ball pocket) of the recommended running route as the y-axis; the distance between two points on the billiard running route and the recommended running route corresponding to the same vertical coordinate is taken as the line distance, and the maximum distance between the two running routes is found; the above maximum distance is compared with the preset distance to determine whether the maximum distance is greater than the preset distance.

[0087] Specifically, if yes, execute step S303; if no, execute step S304.

[0088] Step S303, determining that the billiards running route does not conform to the recommended running route.

[0089] Step S304, determining whether the billiard ball running route conforms to the recommended running route.

[0090] Preferably, Figure 4 FIG. 4 is a flow chart showing a method for determining an initial speed according to an embodiment of the present invention. Figure 4 As shown, the method includes:

[0091] Step S401 compares the running initial speed with the recommended initial speed to determine the maximum speed difference between the two.

[0092] Step S402, calculating the speed difference ratio between the maximum speed difference and the recommended initial speed, and determining whether the speed difference ratio is greater than a preset ratio.

[0093] Specifically, if yes, execute step S403; if no, execute step S404.

[0094] Step S403, determining that the initial speed of operation does not meet the recommended initial speed.

[0095] Step S404, determining whether the initial speed of operation meets the recommended initial speed.

[0096] Based on the above two methods, it is determined whether the running route and initial speed of the billiard ball meet the corresponding recommended running route and initial speed, and accordingly, step S203 is executed.

[0097] Step S203, judging whether the training person's shot meets the recommended shot data according to the comparison result, and obtaining a judgment result.

[0098] Preferably, based on the comparison between the billiard ball running route and initial running speed and the corresponding recommended hitting data, it is determined whether the hitting is in accordance with the recommended hitting data or which hitting data is in accordance with the corresponding recommended hitting data, and based on this, it is further determined whether the hitting direction and hitting strength of the hitting are in accordance with the recommended data.

[0099] According to the above method, by obtaining the billiard ball running route and initial running speed, the corresponding recommended running route and recommended initial speed are obtained, and then the actual route and speed are compared with the recommended route and speed. The calculated parameters are compared with the preset thresholds to determine whether they meet the recommended values. In this way, it is scientifically and accurately determined whether the shot is accurate or whether a certain technical link of the shot is accurate, which improves the accuracy of the overall judgment process and facilitates the subsequent calculation of the overall accuracy.

[0100] Figure 5 A schematic diagram showing a flow chart of a method for counting ball hitting accuracy according to an embodiment of the present invention;

[0101] like Figure 5 As shown, the method comprises the following steps:

[0102] Step S501, obtaining the total number of shots of the trainee during the current training and the judgment result of each shot.

[0103] Step S502, based on the judgment result of each shot, the number of shots that meet the recommended running route and the number of shots that meet the recommended initial speed are calculated.

[0104] Step S503, according to the calculation results, the route accuracy rate of the current training that meets the recommended running route and the speed accuracy rate that meets the recommended initial speed are obtained, so as to obtain the comprehensive training data of the current training.

[0105] Preferably, the comprehensive training data may include at least: the number of strokes that conform to the recommended running route and the corresponding route accuracy, the number of strokes that conform to the recommended initial speed and the corresponding accuracy, and the number of strokes that conform to both the recommended running route and the recommended initial speed and the corresponding speed accuracy.

[0106] According to the above method, by counting the number of shots that meet the recommended running routes and recommended initial speeds during the training session, the overall shot accuracy rate and the accuracy rate of each individual technical link during the training session are comprehensively calculated to clearly reflect the results of the training session.

[0107] Figure 6 A schematic flow chart of a method for determining and outputting training results according to an embodiment of the present invention is shown;

[0108] like Figure 6 As shown, the method comprises the following steps:

[0109] Step S601, comparing the comprehensive training data of the current training with the historical training data of the previous training.

[0110] Preferably, the line accuracy used to reflect the direction of the ball hitting and the speed accuracy used to reflect the force of the ball hitting are determined in the current training; and compared with the corresponding accuracy values ​​in the historical training data.

[0111] Step S602, determining the overall training results of the current training according to the training data comparison result, and outputting it through a multimedia display.

[0112] Preferably, the training status of the current training is determined by comparing the corresponding accuracy values.

[0113] Step S603, determining the training focus of the next training according to the data with lower accuracy in the overall training results, and outputting it through multimedia display.

[0114] Preferably, based on the overall training results of the current training, the technical links with lower accuracy are determined, identified as the training focus of the next training, and output in multimedia form. The output time range is from the completion of the current training to the start of the next training. The specific time is set according to user needs and is not limited here.

[0115] Preferably, the display device may be a display screen or various types of smart terminals, which are not limited here.

[0116] According to the above method, the current training results can be accurately obtained based on the current training data and historical training data, clearly showing the progress of the current training. It can also intuitively reflect the current shortcomings of the trainee and scientifically determine the training focus of subsequent training. This greatly improves the pertinence and scientific nature of the training content, improves the intelligence of the training system, and is very helpful in improving the training effect of the trainee.

[0117] Figure 7 A schematic flow chart of a method for determining the accuracy of a ball hitting action according to an embodiment of the present invention is shown;

[0118] like Figure 7 As shown, the method comprises the following steps:

[0119] Step S701 : comparing the acquired ball-hitting action image of the trainee with the recommended action image.

[0120] Specifically, the batting action image and the recommended action image are decomposed into an xy plane, a yz plane, and an xz plane according to every two coordinate axis planes;

[0121] The coordinates of the feature point k in the xy plane, yz plane and xz plane in the batting action image and the recommended action image are obtained respectively, and the feature point sequence on each plane is obtained; among which, the feature point sequence in the xy plane in the batting action image is The feature point sequence in the xy plane of the recommended action image is The sequence of feature points in the xz plane is: The feature point sequence in the xz plane in the recommended action image is The feature point sequence of the yz plane is The feature point sequence in the yz plane of the recommended action image is

[0122] Step S702: determining consistency parameters between the batting action image and the recommended action image.

[0123] Specifically, the distances l between the corresponding feature points of the batting action image and the recommended action image on the xy plane, yz plane, and xz plane are calculated respectively.

[0124]

[0125] Where n is the number of feature points on the plane; are the coordinates of the i-th feature point in the batting action image; are the coordinates of the i-th feature point in the recommended action image;

[0126] According to the distances of feature points on the xy plane, yz plane and xz plane, the feature distance L of the feature point is calculated.

[0127]

[0128] Among them, l i That is, the distance between the corresponding feature points on the xy plane, the yz plane, and each of the xz planes;

[0129] The feature distance L is used as a consistency parameter and combined with preset parameters to determine whether the batting action image conforms to the recommended action image.

[0130] Step S703, judging whether the batting action image conforms to the recommended action image according to the consistency parameter and the preset parameter, so as to provide the statistical module with statistical action accuracy.

[0131] Preferably, the action accuracy is also included in the training data, and if the action accuracy is lower than the line accuracy or the speed accuracy, the action training can be used as the training focus of the next training.

[0132] According to the above method, the trainee's movement accuracy can be accurately judged through consistency parameters to obtain the movement accuracy rate, which further improves the content of the training data so that it can guide subsequent training more specifically and help improve the trainee's training effect.

[0133] Figure 8 A schematic flow chart of a method for tracking and analyzing billiards training data according to an embodiment of the present invention is shown;

[0134] like Figure 8 As shown, the method comprises the following steps:

[0135] Step S801, obtaining the trainee's hitting action image and the corresponding billiard ball running route and initial running speed based on the camera.

[0136] Specifically, the billiard ball running route at least includes a white ball running route and a target ball running route; the running initial speed is the white ball running initial speed;

[0137] According to the trainee's hitting action and the corresponding billiard ball running route and initial running speed.

[0138] Step S802, based on the recommended hitting data generated for each hitting, combined with the trainee's hitting action image and the corresponding billiard ball running line and initial running speed, determine whether the hitting is in accordance with the recommended hitting data to obtain a determination result.

[0139] Specifically, the method further comprises:

[0140] Determine recommended hitting data according to the hitting action image; wherein the recommended hitting data at least includes a recommended running route and a recommended initial speed;

[0141] Based on the recommended hitting data, the trainee's billiard ball running route and initial running speed are compared with the obtained recommended hitting data;

[0142] According to the comparison result, it is judged whether the training person's hitting of the ball meets the recommended hitting data, and a judgment result is obtained.

[0143] Specifically, the method further comprises:

[0144] Compare the billiard running line with the recommended running line to determine the maximum distance between the two running lines;

[0145] Determine whether the maximum spacing is greater than the preset spacing; if so, determine that the billiards running route does not conform to the recommended running route; if not, determine that the billiards running route conforms to the recommended running route;

[0146] Compare the initial running speed with the recommended initial speed to determine the maximum speed difference between the two;

[0147] Calculate the speed difference ratio between the maximum speed difference and the recommended initial speed, and determine whether the speed difference ratio is greater than a preset ratio; if so, determine that the running initial speed does not meet the recommended initial speed; if not, determine that the running initial speed meets the recommended initial speed.

[0148] Step S803, according to the judgment result of each hitting, the comprehensive training data of the current training is counted.

[0149] Specifically, the method further comprises:

[0150] Obtain the total number of hits of the trainee during the training and the judgment result of each hit;

[0151] Based on the judgment result of each shot, the number of shots that meet the recommended running line and the number of shots that meet the recommended initial speed are calculated;

[0152] According to the calculation results, the route accuracy rate of the training that meets the recommended running route and the speed accuracy rate that meets the recommended initial speed are obtained, so as to obtain the comprehensive training data of the training.

[0153] Specifically, the method further includes:

[0154] Based on the acquired batting action image of the trainee, the batting action image is compared with the recommended action image;

[0155] Determine consistency parameters between the batting action image and the recommended action image;

[0156] According to the consistency parameter and the preset parameter, it is judged whether the batting action image conforms to the recommended action image, so as to provide the statistical module with statistical action accuracy.

[0157] Preferably, the batting action image and the recommended action image are decomposed into an xy plane, a yz plane and an xz plane according to every two coordinate axis planes;

[0158] The coordinates of the feature point k in the xy plane, yz plane and xz plane in the batting action image and the recommended action image are obtained respectively, and the feature point sequence on each plane is obtained; among which, the feature point sequence in the xy plane in the batting action image is The feature point sequence in the xy plane of the recommended action image is The rest of the planes can be inferred in this way;

[0159] Calculate the distance l between the corresponding feature points of the batting action image and the recommended action image on the xy plane, yz plane, and xz plane respectively

[0160]

[0161] Where n is the number of feature points on the plane; are the coordinates of the i-th feature point in the batting action image; are the coordinates of the i-th feature point in the recommended action image;

[0162] According to the distance of feature points on the xy plane, yz plane and xz plane, calculate the feature distance L of the feature point

[0163]

[0164] Among them, l i That is, the distance between the corresponding feature points on the xy plane, the yz plane, and each of the xz planes;

[0165] The feature distance L is used as a consistency parameter and combined with preset parameters to determine whether the batting action image conforms to the recommended action image.

[0166] Step S804, outputting the comprehensive training data of the current training, and outputting the overall training results of the current training based on the historical training data of the previous training and the comprehensive training data of the current training.

[0167] Specifically, the method further comprises:

[0168] Compare the comprehensive training data of the current training with the historical training data of the previous training;

[0169] Determine the overall training results of the current training according to the training data comparison results, and output them through multimedia display;

[0170] The training focus for the next training session is determined based on the data with lower accuracy in the overall training results, and is output through multimedia display.

[0171] According to a billiards training data tracking and analysis method provided by the present embodiment, a trainee's batting action image and a corresponding billiard ball running line and an initial running speed are obtained based on a camera; based on the recommended batting data generated for each batting, combined with the trainee's batting action image and the corresponding billiard ball running line and an initial running speed, it is judged whether the batting meets the recommended batting data to obtain a judgment result; based on the judgment result of each batting, the comprehensive training data of the current training is counted; the comprehensive training data of the current training is output, and based on the historical training data of the previous training and the comprehensive training data of the current training, the overall training results of the current training are output. The billiards training data tracking and analysis method provided by the present embodiment collects the trainee's batting action image, billiards running line, and running initial speed; uses the batting action image to scientifically determine the recommended batting line and recommended initial speed of the batting; compares the actual running lines of the white ball and the target ball with the recommended batting line; compares the running initial speed of the white ball with the recommended initial speed; based on the distance from the recommended line and the difference ratio with the recommended speed, accurately judges whether the batting route and batting strength of the batting meet the recommended batting data; and then performs a comparison on the training. Statistics are used to determine the accuracy of the hitting line and hitting force of the current training, which are used as the training data of the current training; by comparing the current training data with the historical training data, the training results of the current training are scientifically determined, clearly showing the progress of the trainee in the current training compared with the previous training, and also reflecting the aspects that still need to be improved, which are used as the key items of the next training, and based on this, the training method suitable for the current situation of the trainee is intelligently and targetedly determined, which greatly improves the adaptability and scientificity of the training, and thus effectively improves the training effect, and also greatly improves the intelligence of billiards training. At the same time, based on the feature point sequence in the hitting action image and the recommended action image, the consistency parameter is calculated to scientifically determine whether the hitting action image conforms to the recommended action image, to intelligently judge the accuracy of the trainee's hitting action, so as to assist the system in determining the overall action accuracy in the current training, and further select the focus of the next training, further improving the scientificity of the training.

[0172] Fig. 9 FIG. 4 shows a schematic diagram of the structure of a billiard table according to an embodiment of the present invention. Fig. 9 As shown, the billiard table uses the above-mentioned billiard training data tracking and analysis system, including: a table body 901, a guide rail 902 and a placement mechanism 903; wherein,

[0173] The table body further includes: table legs 9011, a table top 9012, a ball bag 9013 and a table edge 9014; wherein the table top 9012 is rectangular;

[0174] The placing mechanism 903 is located on one side of a short side of the rectangular tabletop 9012;

[0175] The guide rail 902 has a downward slope, and it goes around from the two corner pockets on the side where the placement mechanism 903 is located, through the bottom of the ball pockets on each long side, and finally converges at the short side on the other side and connects to the placement mechanism 903.

[0176] Specifically, after the billiard ball falls into the ball pocket 9013, it enters the guide rail 902 and moves along the guide rail 902 to the placement mechanism 903;

[0177] The placing mechanism 9013 is used to place the collected billiard balls at a preset position on the table 9012 according to a preset style after the game is over.

[0178] The billiard table provided in this embodiment automatically gathers the billiard balls entering the ball pockets through guide rails and placement mechanisms, and automatically discharges them after the game is completed, taking over the placement work of the athletes, reducing the time spent between games, and improving the user experience.

[0179] The present invention also provides a non-volatile computer storage medium, which stores at least one executable instruction, and the executable instruction can execute a billiards training data tracking and analysis method in any of the above method embodiments.

[0180] Fig.10 A schematic diagram of the structure of a computing device according to an embodiment of the present invention is shown. The specific embodiment of the present invention does not limit the specific implementation of the computing device.

[0181] like Fig.10 As shown, the computing device may include: a processor (processor) 1002 , a communication interface (Communications Interface) 1004 , a memory (memory) 1006 , and a communication bus 1008 .

[0182] in:

[0183] The processor 1002 , the communication interface 1004 , and the memory 1006 communicate with each other via a communication bus 1008 .

[0184] The communication interface 1004 is used to communicate with other devices such as clients or other servers.

[0185] The processor 1002 is used to execute the program 1010, and specifically can execute the relevant steps in the above-mentioned billiards training data tracking and analysis method embodiment.

[0186] Specifically, the program 1010 may include program codes, and the program codes include computer operation instructions.

[0187] The processor 1002 may be a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present invention. The one or more processors included in the computing device may be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs.

[0188] The memory 1006 is used to store the program 1010. The memory 1006 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0189] Program 1010 can be specifically used to enable processor 1002 to execute a billiard training data tracking and analysis method in any of the above method embodiments. The specific implementation of each step in program 1010 can refer to the corresponding descriptions in the corresponding steps and units in the above billiard training data tracking and analysis method embodiment, which will not be repeated here. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working process of the above-described devices and modules can refer to the corresponding process description in the above-mentioned method embodiment, which will not be repeated here.

[0190] The algorithm and display provided herein are not inherently related to any particular computer, virtual system or other device. Various general purpose systems can also be used together with the teachings based on this. According to the above description, it is obvious that the structure required for constructing such systems. In addition, the present invention is not directed to any specific programming language either. It should be understood that various programming languages ​​can be utilized to realize the content of the present invention described herein, and the description of the above specific languages ​​is for disclosing the best mode of the present invention.

[0191] In the description provided herein, a large number of specific details are described. However, it is understood that embodiments of the present invention can be practiced without these specific details. In some instances, well-known methods, structures and techniques are not shown in detail so as not to obscure the understanding of this description.

[0192] Similarly, it should be understood that in order to streamline the present disclosure and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the present invention, various features of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof. However, this disclosed method should not be interpreted as reflecting the intention that the claimed invention requires more features than those expressly recited in each claim. Rather, as reflected in the claims, inventive aspects lie in less than all of the features of the individual embodiments previously disclosed. Therefore, the claims that follow the detailed description are hereby expressly incorporated into the detailed description, with each claim itself serving as a separate embodiment of the present invention.

[0193] Those skilled in the art will appreciate that the modules in the devices in the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments may be combined into one module or unit or component, and in addition they may be divided into a plurality of submodules or subunits or subcomponents. Except that at least some of such features and / or processes or units are mutually exclusive, all features disclosed in this specification (including the accompanying claims, abstracts and drawings) and all processes or units of any method or device disclosed in this manner may be combined in any combination. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstracts and drawings) may be replaced by an alternative feature providing the same, equivalent or similar purpose.

[0194] In addition, those skilled in the art will appreciate that, although some embodiments described herein include certain features included in other embodiments but not other features, the combination of features of different embodiments is meant to be within the scope of the present invention and form different embodiments. For example, in the claims, any one of the claimed embodiments may be used in any combination.

[0195] The various component embodiments of the present invention can be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It should be understood by those skilled in the art that a microprocessor or digital signal processor (DSP) can be used in practice to implement some or all of the functions of some or all of the components in the embodiments of the present invention. The present invention can also be implemented as a device or apparatus program (e.g., computer program and computer program product) for executing part or all of the methods described herein. Such a program implementing the present invention can be stored on a computer-readable medium, or can have the form of one or more signals. Such a signal can be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.

[0196] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A billiards training data tracking and analysis system, comprising: Acquisition module, judgment module, statistics module and output module; among them, The acquisition module is used to obtain the trainee's hitting action image and the corresponding billiard ball running line and initial running speed based on the camera; The judging module is used to judge whether the shot meets the recommended shot data based on the recommended shot data generated for each shot, in combination with the shot action image of the trainee and the corresponding billiard ball running line and initial running speed, and obtain a judgment result; The statistical module is used to collect the comprehensive training data of the training session according to the judgment result of each shot; The output module is used to output the comprehensive training data of the current training, and output the overall training results of the current training based on the historical training data of the previous training and the comprehensive training data of the current training.

2. The billiards training data tracking and analysis system according to claim 1, characterized in that: The acquisition module is further used for: The billiard ball running path at least includes a white ball running path and a target ball running path; the running initial speed is the white ball running initial speed; According to the trainee's hitting action and the corresponding billiard ball running route and initial running speed.

3. The billiards training data tracking and analysis system according to claim 1, characterized in that: The judging module is further used for: Determine recommended hitting data according to the hitting action image; wherein the recommended hitting data at least includes a recommended running route and a recommended initial speed; Based on the recommended hitting data, the trainee's billiard ball running route and initial running speed are compared with the obtained recommended hitting data; According to the comparison result, it is judged whether the training person's hitting of the ball meets the recommended hitting data, and a judgment result is obtained.

4. The billiards training data tracking and analysis system according to claim 1, characterized in that: The judging module is further used for: Compare the billiard running line with the recommended running line to determine the maximum distance between the two running lines; Determine whether the maximum spacing is greater than the preset spacing; If so, it is determined that the billiard ball running route does not conform to the recommended running route; If not, it is determined that the billiard ball running route conforms to the recommended running route; Compare the initial running speed with the recommended initial speed to determine the maximum speed difference between the two; Calculate the speed difference ratio between the maximum speed difference and the recommended initial speed, and determine whether the speed difference ratio is greater than a preset ratio; If so, it is determined that the initial speed of operation does not meet the recommended initial speed; If not, it is determined that the initial speed of operation meets the recommended initial speed.

5. The billiards training data tracking and analysis system according to claim 1, characterized in that: The statistical module is further used for: Obtain the total number of hits of the trainee during the training and the judgment result of each hit; Based on the judgment result of each shot, the number of shots that meet the recommended running line and the number of shots that meet the recommended initial speed are calculated; According to the calculation results, the route accuracy rate of the training that meets the recommended running route and the speed accuracy rate that meets the recommended initial speed are obtained, so as to obtain the comprehensive training data of the training.

6. The billiards training data tracking and analysis system according to claim 1, characterized in that: The output module is further used for: Compare the comprehensive training data of the current training with the historical training data of the previous training; Determine the overall training results of the current training according to the training data comparison results, and output them through multimedia display; The training focus for the next training session is determined based on the data with lower accuracy in the overall training results, and is output through multimedia display.

7. The billiards training data tracking and analysis system according to claim 1, characterized in that: The judging module is further used for: Based on the acquired batting action image of the trainee, the batting action image is compared with the recommended action image; Determine consistency parameters between the batting action image and the recommended action image; According to the consistency parameter and the preset parameter, it is judged whether the batting action image conforms to the recommended action image, so as to provide the statistical module with statistical action accuracy.

8. The billiards training data tracking and analysis system according to any one of claims 1 to 7, characterized in that: The judging module is further used for: Decompose the batting action image and the recommended action image into an xy plane, a yz plane, and an xz plane according to each two coordinate axis planes; The coordinates of the feature point k in the xy plane, yz plane and xz plane in the batting action image and the recommended action image are obtained respectively, and the feature point sequence on each plane is obtained; among which, the feature point sequence in the xy plane in the batting action image is The feature point sequence in the xy plane of the recommended action image is The rest of the planes can be inferred in this way; Calculate the distance l between the corresponding feature points of the batting action image and the recommended action image on the xy plane, yz plane, and xz plane respectively Where n is the number of feature points on the plane; are the coordinates of the i-th feature point in the batting action image; are the coordinates of the i-th feature point in the recommended action image; According to the distance of feature points on the xy plane, yz plane and xz plane, calculate the feature distance L of the feature point Among them, l i That is, the distance between the corresponding feature points on the xy plane, the yz plane, and each of the xz planes; The feature distance L is used as a consistency parameter and combined with preset parameters to determine whether the batting action image conforms to the recommended action image.

9. A method for tracking and analyzing billiards training data, comprising: Based on the camera, the trainee's hitting action image and the corresponding billiard ball running line and initial running speed are obtained; According to the recommended hitting data generated for each hitting, combined with the hitting action image of the trainee and the corresponding billiard ball running line and initial running speed, it is judged whether the hitting meets the recommended hitting data to obtain a judgment result; According to the judgment result of each shot, the comprehensive training data of the training session is counted; Output the comprehensive training data of the current training, and based on the historical training data of the previous training and the comprehensive training data of the current training, output the overall training results of the current training.

10. A billiard table, the billiard table applying the billiard training data tracking and analysis system according to claim 1, comprising: Table body, guide rails and placement mechanism; among them, The table body further comprises: table legs, a table top, a ball bag and a table edge; wherein the table top is rectangular; The placing mechanism is located on one side of a short side of the rectangular desktop; The guide rail has a downward slope, and respectively goes from the two corner pockets on the side where the placement mechanism is located, passes under the ball pockets on the long sides of each, and finally converges at the short side on the other side and connects to the placement mechanism; Among them, after the billiard ball falls into the ball pocket, it enters the guide rail and runs along the guide rail to the placement mechanism; the placement mechanism is used to place the collected billiard balls at a preset position on the table according to a preset style after the game is over.

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