CN116824041A - Method and system for detecting competition field based on comprehensive physical performance competition content - Google Patents
Method and system for detecting competition field based on comprehensive physical performance competition content Download PDFInfo
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Abstract
The invention discloses a competition field detection method and a system for representing competition contents based on comprehensive physical ability, wherein the detection method comprises the following steps: s1, acquiring image data of a field and equipment according to the requirements of game items; s2, processing image data based on an image processing technology of edge detection, and classifying image data characteristics of a field and equipment; s3, formulating a three-dimensional simulation construction scheme of the competition field, constructing a three-dimensional simulation model of the competition field by using Sketchup modeling software, and testing the three-dimensional simulation model of the competition field according to the image data characteristics and the formulated scheme; s4, recording simulation construction results, and marking the places which do not meet the requirements. According to the invention, the three-dimensional simulation model of the competition field is established, the layout and design of the whole field are visually checked, so that the model is more real and specific, the competition scene can be better previewed, and the rationality of the field design is detected.
Description
Technical Field
The invention relates to the field of detection of a sports competition field, in particular to a method and a system for detecting the competition field based on comprehensive physical performance competition contents.
Background
In recent years, many researchers have been devoted to this research area of sports video analysis. Sports video analytics research serves mainly two major directions of application: one of which is content-based video retrieval and summarization; secondly, technical and tactical analysis and human motion analysis. Specific applications of the former include: semantic event annotation, highlight event extraction, structural analysis and the like are oriented to general common users, and a long sports video can be effectively searched; the latter is faced with professional users and its goal is to assist the coach in tactics and to assist the athlete in training. Ball and player trajectory extraction is a very useful cue for technical and tactical analysis of sports videos. Court detection has a very important role in sports video analysis. Sports video scene classification, object (including ball, athlete, and reticle, etc.) detection, semantic event annotation, highlight event extraction, and sports video structure analysis work, etc. are all highly dependent on the results of course detection. The competition items can design different difficulties, different item numbers and various item categories according to the competition level to comprehensively and comprehensively check physical ability of athletes. Each unit project design does not emphasize that a single muscle group or a single physical dimension repeatedly performs work, but aims at checking the athletic ability of the athlete, and checks the comprehensive ability of the athlete by a multi-number, rapid and explosive method mainly comprising the self weight and the load of various modes.
The comprehensive physical ability project is designed with three general physical attributes: speed, strength, endurance, three basic actions: squatting, pushing and pulling are basic principles; the design of non-intermittent project is performed by integrating a plurality of actions such as weightlifting, gymnastics, track and field, and the design of skill break project is performed by: BALANCE, JUMP, SWING, CLIMB is a basic principle for examining comprehensive ability of athletes. Reliable and accurate playing field area detection is particularly important for analysis of playing fields.
Current playing field detection methods typically use sensors and equipment to detect, but these equipment have limited accuracy and may not accurately identify some minor defects and problems. Therefore, more efficient and accurate detection techniques and devices are further developed to improve the accuracy and effectiveness of field detection, and current competition field detection mainly relies on manual work, and lacks intelligent processing means.
For the problems in the related art, no effective solution has been proposed at present.
Disclosure of Invention
Aiming at the problems in the related art, the invention provides a method and a system for detecting a competition field based on comprehensive physical performance competition contents, which are used for overcoming the technical problems existing in the prior art.
For this purpose, the invention adopts the following specific technical scheme:
according to an aspect of the present invention, there is provided a game field detection method for expressing contents of a competition based on comprehensive physical ability, the game field detection method comprising the steps of:
s1, determining a place and equipment which need to be subjected to simulation construction according to the requirements of the game items, and collecting image data of the place and the equipment;
s2, processing image data based on an image processing technology of edge detection, and classifying image data characteristics of a field and equipment;
s3, formulating a three-dimensional simulation construction scheme of the competition field, constructing a three-dimensional simulation model of the competition field by using Sketchup modeling software, and testing the three-dimensional simulation model of the competition field according to the image data characteristics and the formulated scheme;
s4, recording simulation construction results, marking the places which do not meet the requirements, obtaining detection records and detection reports, and providing the detection records and the detection reports for a game group commission.
Further, the image processing technology based on edge detection processes image data and classifies the image data characteristics of the field and the equipment, and comprises the following steps:
s21, carrying out graying treatment on the image to obtain gray image data;
s22, carrying out Gaussian smoothing on the gray level image and calculating the gradient and the direction of each pixel point;
s23, performing non-maximum value inhibition based on the gradient value and the threshold value, and regarding pixel points with the inhibited gradient value larger than the set threshold value as edge points;
s24, dividing the areas of the extracted edge points by using a Canny edge detection algorithm to obtain image data characteristics.
Further, the step of performing the gaussian smoothing on the gray image and calculating the gradient and the direction of each pixel point includes the following steps:
s221, reading a gray level image, and defining a Gaussian kernel;
s222, placing Gaussian kernels on each pixel point of an image, and performing convolution operation;
s223, in the convolution process, carrying out boundary expansion processing on pixel points falling on the edge to obtain a smooth gray level image;
s224, calculating gradients of pixel points of each gray level image in the x and y directions by utilizing a Sobel operator to obtain gradient amplitude and direction information;
the method for calculating the gradient of the pixel point of each gray level image in the x and y directions by utilizing the Sobel operator to obtain gradient amplitude and direction information comprises the following steps:
s2241, calculating a Sobel operator in the horizontal direction by making a difference between the gray values of the pixel points and the surrounding pixel points, and obtaining a gray difference value of the pixel points in the horizontal direction;
s2242, calculating a Sobel operator in the vertical direction by making a difference between the gray values of the pixel points and the surrounding pixel points, and obtaining a gray difference value of the pixel points in the vertical direction;
s2243, combining the gray level difference value in the horizontal direction and the gray level difference value in the vertical direction to obtain the gradient amplitude value and the gradient direction of the pixel point;
the gradient amplitude is obtained by calculating the square sum of gradient values in two directions and then opening the root number;
the gradient direction is obtained by calculating the ratio of the gradient values in the two directions and the arctangent function.
Further, the method for dividing the extracted edge points into areas by using a Canny edge detection algorithm to obtain image data features comprises the following steps:
s241, carrying out Canny edge detection on the edge points to obtain a set of the edge points in the gray image data;
s242, clustering operation is carried out on the edge points, and the edge points with adjacent distances are divided into the same group to obtain an edge point group;
s243, calculating convex hulls and minimum circumscribed rectangles of the edge point groups, and obtaining characteristic information of each region in the gray image data according to the convex hulls and the minimum circumscribed rectangles of the edge point groups.
Further, the step of establishing a three-dimensional simulation construction scheme of the competition field, utilizing Sketchup modeling software to construct a three-dimensional simulation model of the competition field, and according to the image data characteristics and the established scheme, testing the three-dimensional simulation model of the competition field comprises the following steps:
s31, the requirements of the comprehensive physical performance competition content are clarified, data and information of a competition field, equipment and players are collected and processed, and a three-dimensional simulation construction scheme is formulated;
s32, acquiring image data and information of a competition field, and using Sketchup modeling software to formulate a three-dimensional modeling construction scheme;
s33, constructing a three-dimensional simulation model of the competition area in Sketchup according to a three-dimensional simulation construction scheme;
s34, comparing the three-dimensional simulation model construction of the competition field to test, and judging whether the expected requirement is met.
Further, the step of acquiring the image data and information of the game field and using Sketchup modeling software to formulate a three-dimensional modeling construction scheme comprises the following steps:
s321, collecting a plan view, an elevation view, equipment parameters and player performance data of the competition area;
s322, using the plan view and the elevation view as the foundation structure of the field, and drawing the main structure of the field, the space structure and the space size of the seat and the ladder base by selecting a three-dimensional tool;
s323, adding models of equipment, props and moving objects into the three-dimensional model of the competition field, and adjusting the proportion, angle and position parameters of the models to ensure that the three-dimensional space is consistent with the competition field.
Further, according to the three-dimensional simulation construction scheme, the construction of the three-dimensional simulation model of the playing field in Sketchup comprises the following steps:
s331, opening Sketchup software and creating a new document, acquiring all entities, traversing the surface, group and group data in the new document, and obtaining three types of information according to the traversal, wherein the steps are as follows;
s332, carrying out calculation and analysis on the surface to obtain relative coordinates, normal lines, front and back materials and hole information, and if the hole information exists, carrying out triangulation in the SKP data extraction stage according to the requirement to obtain a triangular surface for storage, or directly storing the surface profile information containing the hole and the profile information of the hole;
s333, extracting all entities in the group by using SUGroupGet entities, and continuing to start recursion circulation from the step S331;
s334, continuing to start a recursion cycle from the step S331 by using all entities in the extraction component;
s335, extracting data from the Skp model file through secondary development, and analyzing the plan view, the elevation view, the equipment parameters and the player performance data of the playing field based on the SUModelGet entity.
Further, the data is extracted from the Skp model file through secondary development, and the plan view, the elevation view, the equipment parameters and the player performance data analysis of the playing field based on the sumodeget entity comprise the following steps:
s3351, loading the Skp model file into an object of a SUModelRef type by using a SUModelCreateFromFile function;
s3352, obtaining a SUEntitiesRef entity set from a SUModelRef object by using a SUModelGet entity function, wherein the entity comprises elements of a plane, a line and a curve in the model;
s3353, traversing the entity and checking whether the needed component or group information exists;
s3354, generating a plan view of the playing field by processing the assembly or group information, and displaying the position, shape and size information of each area of the field;
s3355, sampling elevation information of SUEdgeRef boundary lines of a competition field with high and low fluctuation, and drawing an elevation graph to display the change condition of the height of the field;
s3356, obtaining information of equipment parameters and player performances by processing elements of the SUFaceRef plane, the SUEdgeRef boundary line and the SUVertexRef vertex, traversing sub-components in the component by using a SUComponentInstanceGetChildCount function, and recording types and parameter information of the sub-components.
Further, the step of comparing the three-dimensional simulation model construction of the competition field to test and judging whether the competition field meets the expected requirement comprises the following steps:
s341, importing test data of player performance data and equipment parameters into a model to perform various tests;
s342, checking whether the test result accords with expectations according to the authenticity of the competition process, the accuracy of player performance data and the accuracy of equipment parameters;
s343, if a problem occurs in the competition area, recording the problem and marking the problem;
and S344, repairing the found problems, and retesting until the requirements are met.
According to another aspect of the present invention, there is also provided a competition field detection system based on comprehensive physical performance competition contents, the system including a field and equipment image data acquisition module, an image processing and classifying module, a three-dimensional modeling construction module, and a result recording and reporting module;
the field and equipment image data acquisition module is used for determining the field and equipment which need to be constructed in a simulation mode according to the requirements of the game items and acquiring the image data of the field and the equipment;
the image processing and classifying module is used for processing the image data based on the image processing technology of edge detection and classifying the image data characteristics of the field and the equipment;
the three-dimensional simulation construction module is used for making a three-dimensional simulation construction scheme of the competition field, constructing a three-dimensional simulation model of the competition field by using Sketchup modeling software, and testing the three-dimensional simulation model of the competition field according to the image data characteristics and the made scheme;
the result recording and reporting module is used for recording the simulation construction result, marking the place which does not meet the requirement, obtaining the detection record and the detection report, and providing the detection record and the detection report for the game group commission.
The beneficial effects of the invention are as follows:
1. the image processing technology based on edge detection can rapidly extract key characteristic information of the field and equipment from the image, process a large amount of image data in a short time, improve the efficiency of field detection, help clearly separate object boundaries, more accurately locate and analyze the field characteristics during field detection, identify some tiny defects and problems, improve the precision of field detection, and obtain more visual and image field image characteristics and equipment state information by classifying and processing the image data. The information can better help staff to manage and maintain the sites, and the image processing technology based on edge detection has high flexibility and supports detection and classification of different types of sites and equipment. Meanwhile, secondary development and adjustment can be performed according to the needs to meet the requirements of actual scenes, the edge detection technology can automatically process image data, manual intervention and errors are reduced, the automation degree of site detection is improved, and meanwhile detection cost can be reduced.
2. According to the invention, by establishing the three-dimensional simulation model of the competition field, the layout and design of the whole field can be visually checked, and elements such as competition equipment, facilities and the like are added in the model, so that the model is more real and specific, the competition scene can be better previewed, and the rationality of the field design can be detected; the three-dimensional simulation model of the competition field can be used for carrying out simulation experiments in a virtual environment, comparing different field designs and layouts, and optimizing the arrangement, adjustment and the like of equipment. Therefore, errors and risks can be reduced in the actual operation process, and the competition efficiency and safety are improved; after the three-dimensional simulation model of the competition field is established, the field can be tested according to the scheme established before, whether various indexes meet the requirements is analyzed, potential problems and defects are found in time, and corresponding improvement suggestions are provided; sketchup modeling software is taken as professional three-dimensional modeling software, has good visualization tool, can perform fine modeling compared with a competition field, supports adding special effects such as color, texture, illumination and the like, and can intuitively display the distance and the relation between different objects in the model; the site elements can be flexibly added and removed by using modeling software such as Sketchup and the like for modeling, so that the site model can be quickly and conveniently updated. Meanwhile, the three-dimensional simulation model can be modified and adjusted again according to the requirement so as to meet the requirement of an actual scene.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method of playing a game field based on integrated performance of content of the game according to an embodiment of the present invention.
Detailed Description
For the purpose of further illustrating the various embodiments, the present invention provides the accompanying drawings, which are a part of the disclosure of the present invention, and which are mainly used to illustrate the embodiments and, together with the description, serve to explain the principles of the embodiments, and with reference to these descriptions, one skilled in the art will recognize other possible implementations and advantages of the present invention, wherein elements are not drawn to scale, and like reference numerals are generally used to designate like elements.
According to the embodiment of the invention, a method and a system for detecting a competition field based on comprehensive physical performance competition content are provided.
The present invention will be further described with reference to the accompanying drawings and detailed description, as shown in fig. 1, according to an embodiment of the present invention, there is provided a game field detection method for representing contents of a competition based on comprehensive physical ability, the game field detection method including the steps of:
s1, determining a place and equipment which need to be subjected to simulation construction according to the requirements of the game items, and collecting image data of the place and the equipment.
Specifically, a data acquisition mode is determined according to actual conditions. For example, data acquisition can be carried out on an actual site and equipment, or remote data acquisition can be carried out in a manner of unmanned aerial vehicle, vehicle-mounted camera and the like; different image processing technologies can be selected for processing aiming at different types of sites and equipment so as to ensure the quality of image data and the accuracy of feature extraction; for some places and equipment related to sensitive information such as personal privacy, the problems of data privacy protection, such as desensitization treatment on the data, need to be considered; for a large amount of image data, a reasonable data storage scheme needs to be formulated so as to facilitate subsequent data analysis and mining; in order to facilitate subsequent data management and inquiry, a scientific and complete data index and classification system needs to be established so as to quickly locate the required data; corresponding data annotation and annotation are needed for different types of sites and equipment so as to facilitate subsequent data analysis and mining; in the data acquisition process, the quality of the data needs to be monitored in real time, and problems possibly existing in the data acquisition process are found and corrected in time so as to ensure the quality and accuracy of the acquired data.
S2, processing image data based on an image processing technology of edge detection, and classifying image data characteristics of a field and equipment;
in one embodiment, the image processing technique based on edge detection processes image data and classifies image data features of sites and devices comprising the steps of:
s21, carrying out graying treatment on the image to obtain gray image data;
s22, carrying out Gaussian smoothing on the gray level image and calculating the gradient and the direction of each pixel point;
s23, performing non-maximum value inhibition based on the gradient value and the threshold value, and regarding pixel points with the inhibited gradient value larger than the set threshold value as edge points;
s24, dividing the areas of the extracted edge points by using a Canny edge detection algorithm to obtain image data characteristics.
In one embodiment, the gaussian smoothing of the gray-scale image and calculating the gradient and direction of each pixel point includes the steps of:
s221, reading a gray level image, and defining a Gaussian kernel;
s222, placing Gaussian kernels on each pixel point of an image, and performing convolution operation;
s223, in the convolution process, carrying out boundary expansion processing on pixel points falling on the edge to obtain a smooth gray level image;
s224, calculating gradients of pixel points of each gray level image in the x and y directions by utilizing a Sobel operator to obtain gradient amplitude and direction information;
the method for calculating the gradient of the pixel point of each gray level image in the x and y directions by utilizing the Sobel operator to obtain gradient amplitude and direction information comprises the following steps:
s2241, calculating a Sobel operator in the horizontal direction by making a difference between the gray values of the pixel points and the surrounding pixel points, and obtaining a gray difference value of the pixel points in the horizontal direction;
s2242, calculating a Sobel operator in the vertical direction by making a difference between the gray values of the pixel points and the surrounding pixel points, and obtaining a gray difference value of the pixel points in the vertical direction;
s2243, combining the gray level difference value in the horizontal direction and the gray level difference value in the vertical direction to obtain the gradient amplitude value and the gradient direction of the pixel point;
the gradient amplitude is obtained by calculating the square sum of gradient values in two directions and then opening the root number;
the gradient direction is obtained by calculating the ratio of the gradient values in the two directions and the arctangent function.
Specifically, the gaussian filter can effectively suppress noise and detail information, so that subsequent gradient calculation is more accurate, and when picture processing is performed, proper algorithms and parameters are selected according to different application scenes, and experimental verification is performed, so that an optimal processing result is obtained.
In one embodiment, the dividing the extracted edge points into areas by using the Canny edge detection algorithm, to obtain the image data features includes the following steps:
s241, carrying out Canny edge detection on the edge points to obtain a set of the edge points in the gray image data;
s242, clustering operation is carried out on the edge points, and the edge points with adjacent distances are divided into the same group to obtain an edge point group;
s243, calculating convex hulls and minimum circumscribed rectangles of the edge point groups, and obtaining characteristic information of each region in the gray image data according to the convex hulls and the minimum circumscribed rectangles of the edge point groups.
Specifically, when edge point cluster segmentation is performed, the influence of noise can be considered, and the noise point is prevented from being mistakenly considered as an effective edge point. Therefore, in practical application, preprocessing operations such as smoothing filtering may be performed on the image to reduce the influence of noise. In addition, for some very complex images, it may be desirable to use more advanced image segmentation algorithms, such as region-growing based segmentation algorithms, connectivity-based segmentation algorithms, and the like.
S3, formulating a three-dimensional simulation construction scheme of the competition field, constructing a three-dimensional simulation model of the competition field by using Sketchup modeling software, and testing the three-dimensional simulation model of the competition field according to the image data characteristics and the formulated scheme;
in one embodiment, the step of establishing a three-dimensional simulation construction scheme of the playing field, utilizing Sketchup modeling software to establish a three-dimensional simulation model of the playing field, and according to the image data characteristics and the established scheme, testing the three-dimensional simulation model of the playing field comprises the following steps:
s31, the requirements of the comprehensive physical performance competition content are clarified, data and information of a competition field, equipment and players are collected and processed, and a three-dimensional simulation construction scheme is formulated;
s32, acquiring image data and information of a competition field, and using Sketchup modeling software to formulate a three-dimensional modeling construction scheme;
s33, constructing a three-dimensional simulation model of the competition area in Sketchup according to a three-dimensional simulation construction scheme;
s34, comparing the three-dimensional simulation model construction of the competition field to test, and judging whether the expected requirement is met.
In one embodiment, the capturing of the game field image data and information, using sknchup modeling software to formulate a three-dimensional modeling build plan includes the steps of:
s321, collecting a plan view, an elevation view, equipment parameters and player performance data of the competition area;
s322, using the plan view and the elevation view as the foundation structure of the field, and drawing the main structure of the field, the space structure and the space size of the seat and the ladder base by selecting a three-dimensional tool;
s323, adding models of equipment, props and moving objects into the three-dimensional model of the competition field, and adjusting the proportion, angle and position parameters of the models to ensure that the three-dimensional space is consistent with the competition field.
In one embodiment, the three-dimensional simulation model construction of the playing field in SketchUp according to the three-dimensional simulation construction scheme comprises the following steps:
s331, opening Sketchup software and creating a new document, acquiring all entities, traversing the surface, group and group data in the new document, and obtaining three types of information according to the traversal, wherein the steps are as follows;
s332, carrying out calculation and analysis on the surface to obtain relative coordinates, normal lines, front and back materials and hole information, and if the hole information exists, carrying out triangulation in the SKP data extraction stage according to the requirement to obtain a triangular surface for storage, or directly storing the surface profile information containing the hole and the profile information of the hole;
s333, extracting all entities in the group by using SUGroupGet entities, and continuing to start recursion circulation from the step S331;
s334, continuing to start a recursion cycle from the step S331 by using all entities in the extraction component;
s335, extracting data from the Skp model file through secondary development, and analyzing the plan view, the elevation view, the equipment parameters and the player performance data of the playing field based on the SUModelGet entity.
In one embodiment, the extracting data from the Skp model file through secondary development and analyzing the plan view, elevation map, equipment parameters and player performance data of the playing field based on the sumodeget entity comprises the steps of:
s3351, loading the Skp model file into an object of a SUModelRef type by using a SUModelCreateFromFile function;
s3352, obtaining a SUEntitiesRef entity set from a SUModelRef object by using a SUModelGet entity function, wherein the entity comprises elements of a plane, a line and a curve in the model;
s3353, traversing the entity and checking whether the needed component or group information exists;
s3354, generating a plan view of the playing field by processing the assembly or group information, and displaying the position, shape and size information of each area of the field;
s3355, sampling elevation information of SUEdgeRef boundary lines of a competition field with high and low fluctuation, and drawing an elevation graph to display the change condition of the height of the field;
s3356, obtaining information of equipment parameters and player performances by processing elements of the SUFaceRef plane, the SUEdgeRef boundary line and the SUVertexRef vertex, traversing sub-components in the component by using a SUComponentInstanceGetChildCount function, and recording types and parameter information of the sub-components.
Specifically, the Skp model file is loaded into an object of the SUModelRef type using the SUModelCreateFrom File function. Wherein "SUModelCreateFromFile" is an API function name, indicating that a SUModelRef object is created from the file; and obtaining a SUEntiteseRef entity set from the SUModelRef object by using a SUModelGet entity function, wherein the entity comprises all surface, line and curve elements in the model. Where "SUModelGet" is an API function name, "entity" refers to various geometric elements in the SketchUp model, such as line segments, patches, etc., and "SUEntitiesRef" is a data type in SketchUpCAPI that represents a collection of entities; the entity is traversed and checked for the presence of the required component or group information. Wherein "traversal" refers to cyclic access to entities, "component" and "group" are ways to organize geometric elements in the Sketchup model, for conveniently grouping multiple elements together and operating as a single element; a plan view of the playing field is generated by processing the component or group information, and the position, shape and size information of each area of the field is displayed. Wherein "plan view" refers to a two-dimensional graphical representation, "position, shape, and size" refers to characteristic attributes of various portions of the playing field, and "process" refers to corresponding operations on the components or groups; for a competition field with high and low fluctuation, the altitude information of the SUEdgeRef boundary line is sampled, and an altitude chart is drawn to display the altitude change condition of the field. Wherein "elevation" refers to an elevation relative to a certain datum, "sampling" refers to the process of acquiring data points, and "elevation map" refers to a two-dimensional graph showing an elevation distribution; and processing the elements of the SUFaceRef plane, the SUEdgeRef boundary line and the SUVertexRef vertex to obtain information of equipment parameters and player performances, traversing sub-components in the component by using a SUComponentInstanceGetChildCount function, and recording types and parameter information of the sub-components. Where "SUFaceRef face", "SUEdgeRef border line", "suvertetref vertex", etc. are data types in sketchupcaps representing various geometric elements in the model, "equipment parameters" and "player performance information" refer to data information related to equipment and players in the game, "subsurface instgetchild count" is a function in sketchupcaps for returning the number of subcomponents in the component.
In one embodiment, the comparing the three-dimensional simulation model construction of the competition area to test and determine whether the competition area meets the expected requirement comprises the following steps:
s341, importing test data of player performance data and equipment parameters into a model to perform various tests;
s342, checking whether the test result accords with expectations according to the authenticity of the competition process, the accuracy of player performance data and the accuracy of equipment parameters;
s343, if a problem occurs in the competition area, recording the problem and marking the problem;
and S344, repairing the found problems, and retesting until the requirements are met.
S4, recording simulation construction results, marking the places which do not meet the requirements, obtaining detection records and detection reports, and providing the detection records and the detection reports for a game group commission.
Specifically, the simulation construction result is comprehensively checked and evaluated, and places which do not meet the requirements are marked and recorded according to the competition requirements and regulations; the construction results are evaluated both in terms of overall and detail. In general, it is desirable to evaluate whether the structural, material, dimensions, proportions, etc. of the construct are satisfactory; from the aspect of detail, whether the aspects of surface quality, local detail, joint arrangement and the like of the construction meet the requirements or not needs to be evaluated; detailed description and recording of each unsatisfactory place, including information on the location of the problem, the nature, extent and influence of the problem, etc.; integrating all detection records, compiling a detection report, including two parts of content of integral evaluation and detail evaluation, and providing corresponding improvement measures and suggestions for different problems so as to facilitate subsequent correction and perfection of competitors; and submitting the detection report to a game group committee for auditing and evaluation to determine whether the construction result meets the game requirement and performing final performance evaluation.
According to another embodiment of the present invention, there is further provided a game field detection system for representing contents of a competition based on integrated physical performance, the system including a field and equipment image data acquisition module, an image processing and classifying module, a three-dimensional modeling construction module, and a result recording and reporting module;
the field and equipment image data acquisition module is used for determining the field and equipment which need to be constructed in a simulation mode according to the requirements of the game items and acquiring the image data of the field and the equipment;
the image processing and classifying module is used for processing the image data based on the image processing technology of edge detection and classifying the image data characteristics of the field and the equipment;
the three-dimensional simulation construction module is used for making a three-dimensional simulation construction scheme of the competition field, constructing a three-dimensional simulation model of the competition field by using Sketchup modeling software, and testing the three-dimensional simulation model of the competition field according to the image data characteristics and the made scheme;
the result recording and reporting module is used for recording the simulation construction result, marking the place which does not meet the requirement, obtaining the detection record and the detection report, and providing the detection record and the detection report for the game group commission.
In summary, by means of the above technical scheme, the image processing technology based on edge detection can rapidly extract key feature information of a field and equipment from an image, process a large amount of image data in a short time, improve the efficiency of field detection, help clearly separate object boundaries, locate and analyze the field features more accurately during field detection, identify some tiny defects and problems, improve the accuracy of field detection, and obtain more visual and visual field image features and equipment state information by classifying and processing the image data. The information can better help staff to manage and maintain the sites, and the image processing technology based on edge detection has high flexibility and supports detection and classification of different types of sites and equipment. Meanwhile, secondary development and adjustment can be performed according to the needs to meet the requirements of actual scenes, the edge detection technology can automatically process image data, manual intervention and errors are reduced, the automation degree of site detection is improved, and meanwhile the detection cost can be reduced; according to the invention, by establishing the three-dimensional simulation model of the competition field, the layout and design of the whole field can be visually checked, and elements such as competition equipment, facilities and the like are added in the model, so that the model is more real and specific, the competition scene can be better previewed, and the rationality of the field design can be detected; the three-dimensional simulation model of the competition field can be used for carrying out simulation experiments in a virtual environment, comparing different field designs and layouts, and optimizing the arrangement, adjustment and the like of equipment. Therefore, errors and risks can be reduced in the actual operation process, and the competition efficiency and safety are improved; after the three-dimensional simulation model of the competition field is established, the field can be tested according to the scheme established before, whether various indexes meet the requirements is analyzed, potential problems and defects are found in time, and corresponding improvement suggestions are provided; sketchup modeling software is taken as professional three-dimensional modeling software, has good visualization tool, can perform fine modeling compared with a competition field, supports adding special effects such as color, texture, illumination and the like, and can intuitively display the distance and the relation between different objects in the model; the site elements can be flexibly added and removed by using modeling software such as Sketchup and the like for modeling, so that the site model can be quickly and conveniently updated. Meanwhile, the three-dimensional simulation model can be modified and adjusted again according to the requirement so as to meet the requirement of an actual scene.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (8)
1. A competition field detection method for representing competition contents based on comprehensive physical ability is characterized by comprising the following steps:
s1, determining a place and equipment which need to be subjected to simulation construction according to the requirements of the game items, and collecting image data of the place and the equipment;
s2, processing image data based on an image processing technology of edge detection, and classifying image data characteristics of a field and equipment;
s3, formulating a three-dimensional simulation construction scheme of the competition field, constructing a three-dimensional simulation model of the competition field by using Sketchup modeling software, and testing the three-dimensional simulation model of the competition field according to the image data characteristics and the formulated scheme;
s31, the requirements of the comprehensive physical performance competition content are clarified, data and information of a competition field, equipment and players are collected and processed, and a three-dimensional simulation construction scheme is formulated;
s32, acquiring image data and information of a competition field, and using Sketchup modeling software to formulate a three-dimensional modeling construction scheme;
s321, collecting a plan view, an elevation view, equipment parameters and player performance data of the competition area;
s322, using the plan view and the elevation view as the foundation structure of the field, and drawing the main structure of the field, the space structure and the space size of the seat and the ladder base by selecting a three-dimensional tool;
s323, adding models of equipment, props and moving objects into the three-dimensional model of the competition field, and adjusting the proportion, angle and position parameters of the models to ensure that the three-dimensional space is consistent with the competition field;
s33, constructing a three-dimensional simulation model of the competition area in Sketchup according to a three-dimensional simulation construction scheme;
s34, comparing the three-dimensional simulation model construction of the competition field to test, and judging whether the expected requirement is met;
s4, recording simulation construction results, marking the places which do not meet the requirements, obtaining detection records and detection reports, and providing the detection records and the detection reports for a game group commission.
2. A playing field detection method based on comprehensive performance competition contents according to claim 1, wherein the image processing technology based on edge detection processes image data and classifies image data features of fields and devices comprising the steps of:
s21, carrying out graying treatment on the image to obtain gray image data;
s22, carrying out Gaussian smoothing on the gray level image and calculating the gradient and the direction of each pixel point;
s23, performing non-maximum value inhibition based on the gradient value and the threshold value, and regarding pixel points with the inhibited gradient value larger than the set threshold value as edge points;
s24, dividing the areas of the extracted edge points by using a Canny edge detection algorithm to obtain image data characteristics.
3. A method for detecting a playing field based on the comprehensive performance of racing contents according to claim 2, wherein said performing gaussian smoothing on the gray level image and calculating the gradient and direction of each pixel comprises the steps of:
s221, reading a gray level image, and defining a Gaussian kernel;
s222, placing Gaussian kernels on each pixel point of an image, and performing convolution operation;
s223, in the convolution process, carrying out boundary expansion processing on pixel points falling on the edge to obtain a smooth gray level image;
s224, calculating gradients of pixel points of each gray level image in the x and y directions by utilizing a Sobel operator to obtain gradient amplitude and direction information;
the method for calculating the gradient of the pixel point of each gray level image in the x and y directions by utilizing the Sobel operator to obtain gradient amplitude and direction information comprises the following steps:
s2241, calculating a Sobel operator in the horizontal direction by making a difference between the gray values of the pixel points and the surrounding pixel points, and obtaining a gray difference value of the pixel points in the horizontal direction;
s2242, calculating a Sobel operator in the vertical direction by making a difference between the gray values of the pixel points and the surrounding pixel points, and obtaining a gray difference value of the pixel points in the vertical direction;
s2243, combining the gray level difference value in the horizontal direction and the gray level difference value in the vertical direction to obtain the gradient amplitude value and the gradient direction of the pixel point;
the gradient amplitude is obtained by calculating the square sum of gradient values in two directions and then opening the root number;
the gradient direction is obtained by calculating the ratio of the gradient values in the two directions and the arctangent function.
4. The method for detecting a playing field based on comprehensive performance competition contents according to claim 2, wherein the step of dividing the extracted edge points into areas by using a Canny edge detection algorithm to obtain image data features comprises the following steps:
s241, carrying out Canny edge detection on the edge points to obtain a set of the edge points in the gray image data;
s242, clustering operation is carried out on the edge points, and the edge points with adjacent distances are divided into the same group to obtain an edge point group;
s243, calculating convex hulls and minimum circumscribed rectangles of the edge point groups, and obtaining characteristic information of each region in the gray image data according to the convex hulls and the minimum circumscribed rectangles of the edge point groups.
5. The method for detecting a playing field based on comprehensive performance competition contents according to claim 1, wherein the step of performing three-dimensional simulation model construction of the playing field in sknchup according to the three-dimensional simulation construction scheme comprises the following steps:
s331, opening Sketchup software and creating a new document, acquiring all entities, traversing the surface, group and group data in the new document, and obtaining three types of information according to the traversal, wherein the steps are as follows;
s332, carrying out calculation and analysis on the surface to obtain relative coordinates, normal lines, front and back materials and hole information, and if the hole information exists, carrying out triangulation in the SKP data extraction stage according to the requirement to obtain a triangular surface for storage, or directly storing the surface profile information containing the hole and the profile information of the hole;
s333, extracting all entities in the group by using SUGroupGet entities, and continuing to start recursion circulation from the step S331;
s334, continuing to start a recursion cycle from the step S331 by using all entities in the extraction component;
s335, extracting data from the Skp model file through secondary development, and analyzing the plan view, the elevation view, the equipment parameters and the player performance data of the playing field based on the SUModelGet entity.
6. The method for detecting a playing field based on comprehensive performance competition contents according to claim 5, wherein the steps of extracting data from Skp model files through secondary development and analyzing plan view, elevation view, equipment parameters and player performance data of the playing field based on the sumodeget entity comprise the steps of:
s3351, loading the Skp model file into an object of a SUModelRef type by using a SUModelCreateFromFile function;
s3352, obtaining a SUEntitiesRef entity set from a SUModelRef object by using a SUModelGet entity function, wherein the entity comprises elements of a plane, a line and a curve in the model;
s3353, traversing the entity and checking whether the needed component or group information exists;
s3354, generating a plan view of the playing field by processing the assembly or group information, and displaying the position, shape and size information of each area of the field;
s3355, sampling elevation information of SUEdgeRef boundary lines of a competition field with high and low fluctuation, and drawing an elevation graph to display the change condition of the height of the field;
s3356, obtaining information of equipment parameters and player performances by processing elements of the SUFaceRef plane, the SUEdgeRef boundary line and the SUVertexRef vertex, traversing sub-components in the component by using a SUComponentInstanceGetChildCount function, and recording types and parameter information of the sub-components.
7. The method for detecting a competition field based on comprehensive performance competition contents according to claim 1, wherein the step of comparing the three-dimensional simulation model construction of the competition field to test and judging whether the competition field meets the expected requirement comprises the following steps:
s341, importing test data of player performance data and equipment parameters into a model to perform various tests;
s342, checking whether the test result accords with expectations according to the authenticity of the competition process, the accuracy of player performance data and the accuracy of equipment parameters;
s343, if a problem occurs in the competition area, recording the problem and marking the problem;
and S344, repairing the found problems, and retesting until the requirements are met.
8. A competition field detection system based on comprehensive physical performance competition contents, which is used for realizing the detection steps of the competition field detection method based on comprehensive physical performance competition contents in any one of claims 1-7, and is characterized by comprising a field and equipment image data acquisition module, an image processing and classifying module, a three-dimensional simulation construction module and a result recording and reporting module;
the field and equipment image data acquisition module is used for determining the field and equipment which need to be constructed in a simulation mode according to the requirements of the game items and acquiring the image data of the field and the equipment;
the image processing and classifying module is used for processing the image data based on the image processing technology of edge detection and classifying the image data characteristics of the field and the equipment;
the three-dimensional simulation construction module is used for making a three-dimensional simulation construction scheme of the competition field, constructing a three-dimensional simulation model of the competition field by using Sketchup modeling software, and testing the three-dimensional simulation model of the competition field according to the image data characteristics and the made scheme;
the result recording and reporting module is used for recording the simulation construction result, marking the place which does not meet the requirement, obtaining the detection record and the detection report, and providing the detection record and the detection report for the game group commission.
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