CN116824437A - Measurement method and system for seat body forward bend - Google Patents
Measurement method and system for seat body forward bend Download PDFInfo
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- 238000012360 testing method Methods 0.000 claims abstract description 113
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Abstract
The application relates to a method and a system for measuring the anteversion of a seat, wherein the method comprises the following steps: acquiring a video stream of a seat body forward-bending test, and identifying image coordinates of scale marks on a graduated scale of a seat body forward-bending tester and image coordinates of a vernier push plate from a test area of the video stream; calculating a mapping matrix between the three-dimensional coordinates and the image coordinates based on the three-dimensional model and the image coordinates of the cursor push plate; calculating the image coordinates of the score measurement points through a mapping matrix based on the three-dimensional coordinates of the score measurement points in the cursor push plate three-dimensional model; and calculating the seat body forward-bending test score of the tester based on the image coordinates of the scale marks and the image coordinates of the score measurement points. The method solves the problem of how to improve accuracy of seat body forward-bending score measurement, realizes automation of seat body forward-bending measurement, and enables accuracy of score measurement to be higher based on coordinate calculation of a three-dimensional model of a game mark push plate in a seat body forward-bending tester.
Description
Technical Field
The application relates to the field of computer vision, in particular to a seat body forward-bending measurement method and system.
Background
Seat anteversion belongs to the most common examination item of middle school sports. The common sitting body anteflexion equipment is mainly divided into two types, one type is traditional equipment, the equipment of the type does not use electricity, only has one graduated scale and one vernier, the final achievement needs to be checked manually, and errors caused by human errors are easy to occur; another type of equipment is a semi-intelligent equipment with electronic sensors, the ranging principle of the equipment is that a cursor is pushed when a person to be tested moves, the movement of the cursor can shield an infrared grating embedded in the equipment, the sensors can prompt the distance pushed by the body measurement according to the shielded range of the grating, and the type of equipment has the capability of acquiring information electronically, but has a plurality of problems, for example, the data of the equipment still need to be recorded manually and cannot be identified and acquired automatically, which is not beneficial to the preservation and evidence collection of the body measurement results. Furthermore, the measurement accuracy of the device is not high enough.
At present, no effective solution is proposed for the problem of how to improve the accuracy of seat body forward-flexion score measurement in the related art.
Disclosure of Invention
The embodiment of the application provides a seat body forward-bending measuring method and system, which at least solve the problem of measuring and automating how to realize seat body forward-bending in the related technology.
In a first aspect, an embodiment of the present application provides a method for measuring a seat anteversion, the method including:
acquiring a video stream of a seat body forward-bending test, and identifying image coordinates of scale marks on a graduated scale of a seat body forward-bending tester and image coordinates of a vernier push plate from a test area of the video stream;
calculating a mapping matrix between the three-dimensional coordinates and the image coordinates based on the three-dimensional model of the cursor push plate and the image coordinates;
calculating the image coordinates of the achievement measuring points through the mapping matrix based on the three-dimensional coordinates of the achievement measuring points in the vernier push plate three-dimensional model;
and calculating the seat anteversion test score of the tester based on the image coordinates of the scale marks and the image coordinates of the score measurement points.
In some of these embodiments, before identifying the image coordinates of the scale marks on the scale of the seat body forward-flexion tester from the test area of the video stream, the method comprises:
and performing target detection on the video stream through a target detection model based on a convolutional neural network to obtain a test area for the seat body forward-bending test, wherein the test area is an area where a tester and a seat body forward-bending tester are located.
In some of these embodiments, after obtaining a test zone for performing a seat forward flexion test, the method comprises:
and positioning a graduated scale area of the seat body forward-bending tester based on the seat body forward-bending tester in the test area to serve as a new test area.
In some embodiments, the method for obtaining the test area of the seat body forward-bending test by performing target detection on the video stream based on a target detection model of a convolutional neural network comprises:
and detecting the image frames in the video stream frame by frame based on a target detection model of the convolutional neural network to obtain a test area for the seat body forward-bending test in each image frame.
In some of these embodiments, identifying image coordinates of a tick mark on a scale of a seat body forward-flexion tester from a test area of a video stream includes:
the initial image coordinates of scale marks on a scale of the seat body anteversion tester are identified from a test area of a video stream through an optical character identification technology;
and based on the initial image coordinates of the scale marks, the image coordinates of the scale marks are calculated through Hough transformation identification.
In some of these embodiments, based on the three-dimensional model of the cursor push plate and the image coordinates, calculating the mapping matrix between the three-dimensional coordinates and the image coordinates comprises:
and calculating a mapping matrix between the three-dimensional coordinates and the image coordinates through a ransac algorithm based on the three-dimensional model of the cursor push plate and the image coordinates.
In some of these embodiments, calculating the seat body forward-flexion test score of the tester based on the image coordinates of the graduation marks and the image coordinates of the score measurement points includes:
if the score measurement points fall on the scale marks, obtaining seat body forward-bending test scores of the testers based on the scores corresponding to the scale marks;
if the achievement measuring point does not fall on the graduation line, the achievement measuring point is represented by the formula l=d 1 /(d 2 +d 1 )*(l 2 –l 1 )+l 1 Calculating the seat forward-bending test result of the tester, wherein d 1 D, for the distance between the score test point and the previous score line 2 For the distance between the score test point and the latter score line, l 1 For the test result corresponding to the previous scale mark, l 2 And the test result corresponding to the latter scale line is obtained.
In some of these embodiments, after capturing a video stream of the seat forward flexion test, the method includes:
identifying and extracting human skeleton points of a tester from a test area of the video stream, and judging whether the test action of the tester meets a preset test requirement or not based on the human skeleton points;
and under the condition that the testing action of the tester meets the preset testing requirement, calculating the seat forward-bending testing performance of the tester.
In some of these embodiments, obtaining a video stream of a seat forward flexion test comprises:
and acquiring a video stream of the seat forward-bending test through a camera, or acquiring the video stream of the seat forward-bending test from a database.
In a second aspect, an embodiment of the present application provides a measurement system for sitting body anteversion, the system for performing the method of any one of the first aspects above, the system comprising a data acquisition module, an identification extraction module, and a performance calculation module;
the data acquisition module is used for acquiring a video stream of a seat body forward-flexion test;
the identifying and extracting module is used for identifying the image coordinates of scale marks on a scale of the seat body forward-bending tester and the image coordinates of the vernier pushing plate from the testing area of the video stream; calculating a mapping matrix between the three-dimensional coordinates and the image coordinates based on the three-dimensional model of the cursor push plate and the image coordinates; calculating the image coordinates of the achievement measuring points through the mapping matrix based on the three-dimensional coordinates of the achievement measuring points in the vernier push plate three-dimensional model;
the score calculating module is used for calculating and obtaining the seat forward-bending test score of the tester according to the image coordinates of the scale marks and the image coordinates of the score measuring points.
Compared with the related art, the seat body forward-bending measuring method and system provided by the embodiment of the application have the advantages that the video stream of the seat body forward-bending test is obtained, and the image coordinates of the scale marks on the scale of the seat body forward-bending tester and the image coordinates of the vernier pushing plate are identified from the test area of the video stream; calculating a mapping matrix between the three-dimensional coordinates and the image coordinates based on the three-dimensional model and the image coordinates of the cursor push plate; calculating the image coordinates of the score measurement points through a mapping matrix based on the three-dimensional coordinates of the score measurement points in the cursor push plate three-dimensional model; and calculating the seat body forward-bending test score of the tester based on the image coordinates of the scale marks and the image coordinates of the score measurement points. The method solves the problem of how to improve accuracy of seat body forward-bending score measurement, realizes automation of seat body forward-bending measurement, and enables accuracy of score measurement to be higher based on coordinate calculation of a three-dimensional model of a game mark push plate in a seat body forward-bending tester.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:
FIG. 1 is a flow chart of steps of a seat body forward-flexing measurement method according to an embodiment of the present application;
FIG. 2 is a schematic illustration of detecting a localized test region in accordance with an embodiment of the present application;
FIG. 3 is a schematic view of a seat body anteversion tester scale area according to an embodiment of the present application;
FIG. 4 is a block diagram of a seat body forward flexion measurement system in accordance with an embodiment of the present application;
fig. 5 is a schematic view of an internal structure of an electronic device according to an embodiment of the present application.
The attached drawings are identified: 41. a data acquisition module; 42. identifying an extraction module; 43. and a score calculating module.
Detailed Description
The present application will be described and illustrated with reference to the accompanying drawings and examples in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application. All other embodiments, which can be made by a person of ordinary skill in the art based on the embodiments provided by the present application without making any inventive effort, are intended to fall within the scope of the present application.
It is apparent that the drawings in the following description are only some examples or embodiments of the present application, and it is possible for those of ordinary skill in the art to apply the present application to other similar situations according to these drawings without inventive effort. Moreover, it should be appreciated that while such a development effort might be complex and lengthy, it would nevertheless be a routine undertaking of design, fabrication, or manufacture for those of ordinary skill having the benefit of this disclosure, and thus should not be construed as having the benefit of this disclosure.
Reference in the specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is to be expressly and implicitly understood by those of ordinary skill in the art that the described embodiments of the application can be combined with other embodiments without conflict.
Unless defined otherwise, technical or scientific terms used herein should be given the ordinary meaning as understood by one of ordinary skill in the art to which this application belongs. The terms "a," "an," "the," and similar referents in the context of the application are not to be construed as limiting the quantity, but rather as singular or plural. The terms "comprising," "including," "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, article, or apparatus that comprises a list of steps or modules (elements) is not limited to only those steps or elements but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus. The terms "connected," "coupled," and the like in connection with the present application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The term "plurality" as used herein means two or more. "and/or" describes an association relationship of an association object, meaning that there may be three relationships, e.g., "a and/or B" may mean: a exists alone, A and B exist together, and B exists alone. The character "/" generally indicates that the context-dependent object is an "or" relationship. The terms "first," "second," "third," and the like, as used herein, are merely distinguishing between similar objects and not representing a particular ordering of objects.
An embodiment of the present application provides a method for measuring a seat body forward-bending, and fig. 1 is a flowchart of steps of the method for measuring a seat body forward-bending according to an embodiment of the present application, as shown in fig. 1, and the method includes the following steps:
step S102, acquiring a video stream of a seat body forward-bending test, and identifying image coordinates of scale marks on a scale of a seat body forward-bending tester and image coordinates of a vernier push plate from a test area of the video stream;
step S102 specifically includes the steps of: ,
and S21, acquiring a video stream of the seat forward-bending test through a camera, or directly acquiring the video stream of the seat forward-bending test from a database.
If the video stream is collected through the camera, the video stream indicates that the embodiment can output the result of the measurement calculation of the testers in a real-time seat forward-flexing test scene, so that the real-time automatic measurement of the seat forward-flexing is realized; if the video stream is directly obtained from the database, the historical seat body forward-bending test data processed by the embodiment is represented, and the historical seat body forward-bending test results can be recalculated, so that batch and automatic test of the historical test results is realized.
In step 22, fig. 2 is a schematic diagram of detecting and positioning a test area according to an embodiment of the present application, as shown in fig. 2, a test area for performing a seat forward-bending test is obtained by performing target detection on a video stream based on a target detection model of a convolutional neural network, where the test area is an area of a tester for performing seat forward-bending and a seat forward-bending tester.
In step S22, preferably, the image frames in the video stream are detected frame by using the target detection model, so as to obtain a test area for performing the seat forward-flexion test in each image frame.
Step S23, identifying and extracting human skeleton points of a tester from the test area, and judging whether the test action of the tester meets the preset test requirement or not based on the human skeleton points; if the testing action of the tester meets the preset testing requirement, the seat forward-bending testing result calculation of the tester is continued.
It should be noted that, based on the automatic test action of human skeleton points to judge whether the test action of the tester meets the test requirement of sitting body forward flexion, the error caused by human judgment error is reduced, and the human skeleton points of the tester are recognized and extracted in the method based on deep learning.
Step S24, FIG. 3 is a schematic view of the scale area of the seat body forward-bending tester according to the embodiment of the application, and as shown in FIG. 3, the scale area of the seat body forward-bending tester is positioned as a new test area based on the seat body forward-bending tester in the test area; identifying the image coordinates of scale marks on a scale of the seat body forward-bending tester and the image coordinates of the cursor pushing plate from the new test area; the starting scale of the scale may be-20 cm.
Step S24 preferably identifies initial image coordinates of the scale marks on the scale of the seat body forward-flexion tester from the test area by means of optical character recognition technology (OCR, optical Character Recognition); based on the initial image coordinates of the scale marks, the image coordinates of the scale marks are calculated through Hough transformation identification.
The OCR technology is a process of determining the shape of the character by detecting dark and bright modes and then translating the shape into computer characters by a character recognition method; that is, the characters in the paper document are converted into black-white lattice image file by means of optical mode, and the characters in the image are converted into text format by means of recognition software for further editing and processing by means of word processing software. The hough transform is a feature extraction (feature extraction). Hough transforms are used to identify features in found objects, such as: lines. The algorithm is generally described as follows, given an object, the type of shape to be identified, the algorithm performs a vote in a parameter space (parameter space) to determine the shape of the object.
Step S104, calculating a mapping matrix between the three-dimensional coordinates and the image coordinates based on the three-dimensional model and the image coordinates of the cursor push plate;
step S104 is specifically to calculate a mapping matrix between the three-dimensional coordinates and the image coordinates through a ransac algorithm based on the three-dimensional model of the cursor push plate and the image coordinates.
It should be noted that, the ransac algorithm can effectively filter noise data in the cursor push plate image coordinates, so that the mapping between the image coordinates and the three-dimensional coordinates is more accurate, and the accuracy of calculation of the seat body forward-flexion score is improved.
Step S106, calculating the image coordinates of the score measurement points through a mapping matrix based on the three-dimensional coordinates of the score measurement points in the cursor push plate three-dimensional model;
step S108, calculating and obtaining the seat anteversion test result of the tester based on the image coordinates of the scale marks and the image coordinates of the result measuring points.
Step S108, specifically, judging whether the achievement measuring points fall on the scale marks or not;
if the score measuring points fall on the scale marks, the seat body forward-bending test score of the tester is obtained based on the score corresponding to the scale marks;
if the score measurement point does not fall on the tick mark, then the score measurement point is calculated by the formula l=d 1 /(d 2 +d 1 )*(l 2 –l 1 )+l 1 Calculating the seat forward-bending test result of the tester, wherein d 1 D, for the distance between the score test point and the previous score line 2 For the distance between the score test point and the latter score line, l 1 For the test result corresponding to the previous scale mark, l 2 And the test result corresponding to the latter scale line is obtained.
Through the steps S102 to S108 in the embodiment of the application, the accuracy of measuring the seat body forward-bending score is improved, the automation of seat body forward-bending measurement is realized, and the accuracy of measuring the score is higher based on the coordinate calculation of the three-dimensional model of the game mark push plate in the seat body forward-bending tester.
It should be noted that the steps illustrated in the above-described flow or flow diagrams of the figures may be performed in a computer system, such as a set of computer-executable instructions, and that, although a logical order is illustrated in the flow diagrams, in some cases, the steps illustrated or described may be performed in an order other than that illustrated herein.
An embodiment of the present application provides a seat forward-bending measurement system for performing the method of the above embodiment, and fig. 4 is a block diagram of a seat forward-bending measurement system according to an embodiment of the present application, as shown in fig. 4, including a data acquisition module 41, an identification extraction module 42, and a performance calculation module 43;
the data acquisition module 41 is used for acquiring a video stream of the seat body forward-flexion test;
the identification and extraction module 42 is used for identifying the image coordinates of scale marks on a scale of the seat body anteversion tester and the image coordinates of the cursor pushing plate from the test area of the video stream; calculating a mapping matrix between the three-dimensional coordinates and the image coordinates based on the three-dimensional model and the image coordinates of the cursor push plate; calculating the image coordinates of the score measurement points through a mapping matrix based on the three-dimensional coordinates of the score measurement points in the cursor push plate three-dimensional model;
the score calculating module 43 is configured to calculate a seat body forward-flexion test score of the tester according to the image coordinates of the scale mark and the image coordinates of the score measuring point.
The data acquisition module 41, the identification extraction module 42 and the score calculation module 43 in the embodiment of the application solve the problem of how to improve the accuracy of seat forward-flexion score measurement, realize the automation of seat forward-flexion measurement, and enable the accuracy of score measurement to be higher based on the coordinate calculation of the three-dimensional model of the game mark push plate in the seat forward-flexion tester.
The above-described respective modules may be functional modules or program modules, and may be implemented by software or hardware. For modules implemented in hardware, the various modules described above may be located in the same processor; or the above modules may be located in different processors in any combination.
The present embodiment also provides an electronic device comprising a memory having stored therein a computer program and a processor arranged to run the computer program to perform the steps of any of the method embodiments described above.
Optionally, the electronic apparatus may further include a transmission device and an input/output device, where the transmission device is connected to the processor, and the input/output device is connected to the processor.
It should be noted that, specific examples in this embodiment may refer to examples described in the foregoing embodiments and alternative implementations, and this embodiment is not repeated herein.
In addition, in combination with the seat body forward-bending measurement method in the above embodiment, the embodiment of the application can be realized by providing a storage medium. The storage medium has a computer program stored thereon; the computer program, when executed by a processor, implements a method of measuring the anteversion of any of the above embodiments.
In one embodiment, a computer device is provided, which may be a terminal. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by the processor to implement a method of measuring seat body forward flexion. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
In one embodiment, fig. 5 is a schematic diagram of an internal structure of an electronic device according to an embodiment of the present application, and as shown in fig. 5, an electronic device, which may be a server, is provided, and an internal structure diagram thereof may be as shown in fig. 5. The electronic device includes a processor, a network interface, an internal memory, and a non-volatile memory connected by an internal bus, where the non-volatile memory stores an operating system, computer programs, and a database. The processor is used for providing computing and control capability, the network interface is used for communicating with an external terminal through network connection, the internal memory is used for providing environment for the operation of an operating system and a computer program, the computer program is executed by the processor to realize a seat forward-bending measuring method, and the database is used for storing data.
It will be appreciated by those skilled in the art that the structure shown in fig. 5 is merely a block diagram of a portion of the structure associated with the present inventive arrangements and is not limiting of the electronic device to which the present inventive arrangements are applied, and that a particular electronic device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
It should be understood by those skilled in the art that the technical features of the above-described embodiments may be combined in any manner, and for brevity, all of the possible combinations of the technical features of the above-described embodiments are not described, however, they should be considered as being within the scope of the description provided herein, as long as there is no contradiction between the combinations of the technical features.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
Claims (10)
1. A method of measuring anteversion of a seat, the method comprising:
acquiring a video stream of a seat body forward-bending test, and identifying image coordinates of scale marks on a graduated scale of a seat body forward-bending tester and image coordinates of a vernier push plate from a test area of the video stream;
calculating a mapping matrix between the three-dimensional coordinates and the image coordinates based on the three-dimensional model of the cursor push plate and the image coordinates;
calculating the image coordinates of the achievement measuring points through the mapping matrix based on the three-dimensional coordinates of the achievement measuring points in the vernier push plate three-dimensional model;
and calculating the seat anteversion test score of the tester based on the image coordinates of the scale marks and the image coordinates of the score measurement points.
2. The method of claim 1, wherein prior to identifying image coordinates of a scale mark on a scale of a seat body forward-flexion tester from a test area of a video stream, the method comprises:
and performing target detection on the video stream through a target detection model based on a convolutional neural network to obtain a test area for the seat body forward-bending test, wherein the test area is an area where a tester and a seat body forward-bending tester are located.
3. The method according to claim 2, wherein after obtaining a test zone for performing a seat anteversion test, the method comprises:
and positioning a graduated scale area of the seat body forward-bending tester based on the seat body forward-bending tester in the test area to serve as a new test area.
4. The method of claim 2, wherein obtaining a test area for a seat anteversion test by object detection of the video stream based on an object detection model of a convolutional neural network comprises:
and detecting the image frames in the video stream frame by frame based on a target detection model of the convolutional neural network to obtain a test area for the seat body forward-bending test in each image frame.
5. The method of claim 1, wherein identifying image coordinates of a scale mark on a scale of a seat body forward-flexion tester from a test area of a video stream comprises:
the initial image coordinates of scale marks on a scale of the seat body anteversion tester are identified from a test area of a video stream through an optical character identification technology;
and based on the initial image coordinates of the scale marks, the image coordinates of the scale marks are calculated through Hough transformation identification.
6. The method of claim 1, wherein calculating a mapping matrix between three-dimensional coordinates and image coordinates based on the three-dimensional model of the cursor push plate and the image coordinates comprises:
and calculating a mapping matrix between the three-dimensional coordinates and the image coordinates through a ransac algorithm based on the three-dimensional model of the cursor push plate and the image coordinates.
7. The method of claim 1, wherein calculating a seat body forward-flexion test score for the tester based on the image coordinates of the tick marks and the image coordinates of the score measurement points comprises:
if the score measurement points fall on the scale marks, obtaining seat body forward-bending test scores of the testers based on the scores corresponding to the scale marks;
if the achievement measuring point does not fall on the graduation line, the achievement measuring point is represented by the formula l=d 1 /(d 2 +d 1 )*(l 2 –l 1 )+l 1 Calculating the seat forward-bending test result of the tester, wherein d 1 D, for the distance between the score test point and the previous score line 2 For the distance between the score test point and the latter score line, l 1 For the test result corresponding to the previous scale mark, l 2 And the test result corresponding to the latter scale line is obtained.
8. The method of claim 1, wherein after capturing a video stream of a seat anteversion test, the method comprises:
identifying and extracting human skeleton points of a tester from a test area of the video stream, and judging whether the test action of the tester meets a preset test requirement or not based on the human skeleton points;
and under the condition that the testing action of the tester meets the preset testing requirement, calculating the seat forward-bending testing performance of the tester.
9. The method of claim 1, wherein acquiring a video stream of a seat anteversion test comprises:
and acquiring a video stream of the seat forward-bending test through a camera, or acquiring the video stream of the seat forward-bending test from a database.
10. A measurement system of sitting body anteversion, characterized in that it is adapted to perform the method of any one of claims 1 to 9, said system comprising a data acquisition module, an identification extraction module and a performance calculation module;
the data acquisition module is used for acquiring a video stream of a seat body forward-flexion test;
the identifying and extracting module is used for identifying the image coordinates of scale marks on a scale of the seat body forward-bending tester and the image coordinates of the vernier pushing plate from the testing area of the video stream; calculating a mapping matrix between the three-dimensional coordinates and the image coordinates based on the three-dimensional model of the cursor push plate and the image coordinates; calculating the image coordinates of the achievement measuring points through the mapping matrix based on the three-dimensional coordinates of the achievement measuring points in the vernier push plate three-dimensional model;
the score calculating module is used for calculating and obtaining the seat forward-bending test score of the tester according to the image coordinates of the scale marks and the image coordinates of the score measuring points.
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