A method and system for collecting dummy data

Abstract

The present invention provides a method and system for collecting dummy data, which includes the following steps: marking a dummy and obtaining standard model data of the dummy by scanning; obtaining identifiable feature points of the dummy in a target environment by scanning to obtain partial model data of the dummy; performing alignment processing based on common feature points in the partial model data and the standard model data to obtain complete model data; and measuring and obtaining H-point data of the dummy in the target environment based on the complete model data. By obtaining the complete model data of the dummy in the target environment, breaking through the constraints of the environment, and then measuring and obtaining the H-point data of the dummy in the target environment, the technical reference value of the visualization data for newly developed products is greatly improved, and the technical support for the analysis of competing vehicles is improved. At the same time, the above-mentioned standard model data can be saved and reused, and the relevant model data of the same dummy in different scenarios is improved to improve data collection and analysis efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of automobile testing, and in particular to a dummy data collection method and system. Background Art

[0002] 3D imaging acquisition, a technology that digitally processes actual components, is an indispensable and important technical support in the trial production and modification of automobiles, or in the process of automobile research and development. In the automotive field, a large amount of competitive vehicle data is needed for reference to analyze the advantages and disadvantages of the products developed by oneself and the competitive products. In the process of collecting 3D data of the whole vehicle, it is usually necessary to use dummies to analyze the space, vision and control of the main driver and rear seats to reversely calculate the design advantages of the competitive vehicles.

[0003] The H point on the dummy model, also called the positioning reference point, determines the angles of the driver's body joints and the positions of the eyes, head contours, hand extensions and interfaces in the car body. Therefore, the H point determines the driver's comfort, maneuverability, safety and vision. It describes the relationship between the driver's various performance and the cab environment during the driving process, and is the key connection link between people, machines and the environment. Therefore, the data collection of the H point on the dummy is particularly important competitive data. The position of the H point is determined by the connection point between the human torso and thigh in the dummy model. The midpoint of the connection line of the left and right H points collected on the model is the actual H point.

[0004] In the prior art, the dummy is usually placed in the driving seat and the equipment is used to directly collect data from multiple angles. During the measurement process, no matter how the equipment is debugged or the car dummy is scanned from multiple angles, due to the limitations of the method and the constraints of the surrounding environment, it is impossible to collect the overall data of the dummy. It is only possible to discard the collection of some data and perform estimation analysis to obtain the estimated H point. In the subsequent data analysis, the data of other positions of the dummy, such as eyes and hands, are usually estimated based on the H point. The H point data itself is the estimated data, and the deviation of other estimated data will be greater. The technical support and persuasiveness for the research and development products are minimal, thus losing its due technical reference value. Summary of the invention

[0005] In view of the deficiencies in the prior art, the object of the present invention is to provide a method and system for collecting dummy data, aiming to solve the technical problem in the prior art that the H-point data of the dummy obtained is inaccurate, affecting the reference value of the data.

[0006] In order to achieve the above object, the present invention is implemented by the following technical scheme: a method for collecting dummy data, comprising the following steps:

[0007] Marking a plurality of characteristic points on the dummy, and acquiring a plurality of image data of the dummy in multiple directions by scanning, each of the image data including a plurality of the characteristic points arranged at intervals;

[0008] Based on the common feature points in each of the image data, a plurality of the image data are spliced ​​to obtain standard model data of the dummy;

[0009] Obtaining a number of identifiable feature points of the dummy in the target environment by scanning, so as to obtain partial model data of the dummy;

[0010] Performing alignment processing based on common feature points in the partial model data and the standard model data to obtain complete model data corresponding to the partial model data;

[0011] The H-point data of the dummy in the target environment is measured based on the complete model data.

[0012] Compared with the prior art, the beneficial effects of the present invention are as follows: first, multiple feature points on the dummy are marked, and multiple image data of the dummy in multiple directions are obtained by scanning. The main purpose of scanning and obtaining the above image data is to collect the above feature points, which is equivalent to converting the complete solid surface image data into a number of separate feature points, and further based on the common feature points in the image data, the multiple image data are spliced ​​to obtain the complete standard model data of the dummy, and then the dummy is placed in the environment of the target driving position. Since the dummy is in a specific target environment, some data is difficult to collect. The corresponding target image data is obtained by scanning the dummy, and then the partial model data of the dummy is obtained. , and then use the previously acquired standard model data, and perform alignment processing based on the common feature points in the partial model data and the standard model data, so as to obtain the complete model data corresponding to the partial model data, that is, the complete model data of the dummy in the target environment, break through the constraints of the environment, and then measure the H-point data of the dummy in the target environment, which greatly improves the technical reference value of visualization data for newly developed products and improves the technical support for the analysis of competing vehicles. At the same time, as long as the feature points on the dummy remain unchanged, the above-mentioned standard model data can be saved and reused, and the relevant model data of the same dummy in different scenarios can be improved to obtain accurate actual H-point data, thereby improving data collection and analysis efficiency.

[0013] According to one aspect of the above technical solution, the step of performing splicing processing on the plurality of image data based on the common feature points in each of the image data to obtain the standard model data of the dummy specifically includes:

[0014] Respectively constructing and processing the plurality of feature points on the first image data and the second image data among the plurality of image data to obtain a visualized first feature surface and a second feature surface, wherein the first image data and the second image data both include a plurality of common feature points that are set corresponding to each other;

[0015] Based on the common feature points in the first feature surface and the second feature surface, the first feature surface and the second feature surface are spliced ​​to obtain partial three-dimensional data of the dummy;

[0016] Repeat the above construction and stitching operations for other image data among the plurality of image data to obtain standard model data of the dummy.

[0017] According to one aspect of the above technical solution, in the step of marking a plurality of feature points on the dummy, the method further comprises:

[0018] The distance between every two adjacent feature points is controlled to be within a preset range, and every three adjacent feature points are not on the same straight line.

[0019] According to one aspect of the above technical solution, the step of obtaining the standard model data of the dummy specifically includes:

[0020] The image data corresponding to each limb part of the dummy are processed separately to obtain standard model data including a plurality of independent limb model data.

[0021] According to one aspect of the above technical solution, the step of aligning the partial model data and the standard model data based on the identifiable feature points to obtain the complete model data corresponding to the partial model data specifically includes:

[0022] The partial model data and the standard model data are imported into the GOM software, and the standard model data is used to overwrite the partial model data through a common point alignment instruction to obtain complete model data corresponding to the partial model data.

[0023] According to one aspect of the above technical solution, the steps of marking multiple feature points on the dummy and acquiring multiple image data of the dummy in multiple directions by scanning specifically include:

[0024] The surface of the dummy is sprayed with a developer, and a plurality of feature points are attached at intervals to mark the dummy;

[0025] The dummy is placed under preset environmental conditions, and the dummy is fully scanned in multiple directions to obtain a plurality of image data containing all the feature points.

[0026] According to one aspect of the above technical solution, the step of obtaining a plurality of identifiable feature points of the dummy in the target environment by scanning to obtain partial model data of the dummy specifically includes:

[0027] Partial model data of the dummy is obtained by scanning a plurality of target image data of the dummy in the target environment and splicing the plurality of target image data based on common identifiable feature points in the target image data.

[0028] On the other hand, the present invention also provides a dummy data collection system, comprising:

[0029] A marking module, used for marking a plurality of characteristic points on the dummy, and obtaining a plurality of image data of the dummy in multiple directions by scanning, each of the image data including a plurality of the characteristic points arranged at intervals;

[0030] A first data module, used for performing splicing processing on a plurality of the image data based on common feature points in each of the image data to obtain standard model data of the dummy;

[0031] A second data module is used to obtain a number of identifiable feature points of the dummy in the target environment by scanning, so as to obtain partial model data of the dummy;

[0032] A processing module, configured to perform alignment processing based on common feature points in the partial model data and the standard model data to obtain complete model data corresponding to the partial model data;

[0033] A measuring module is used to measure and obtain H-point data of the dummy in the target environment based on the complete model data.

[0034] According to one aspect of the above technical solution, the processing module specifically includes:

[0035] A processing unit constructs and processes the feature points in each of the image data in turn to obtain a plurality of visualized feature surface data;

[0036] The splicing unit splices each of the feature surfaces based on the common feature points in the feature surface data to obtain the standard model data of the dummy.

[0037] According to one aspect of the above technical solution, the marking module is further used to: control the distance between every two adjacent feature points to be within a preset range, and control every three adjacent feature points to be on non-same straight line.

[0038] According to one aspect of the above technical solution, the first data module is also used for:

[0039] The image data corresponding to each limb part of the dummy are processed separately to obtain standard model data including a plurality of independent limb model data.

[0040] According to one aspect of the above technical solution, the second data module is also used to: import the partial model data and the standard model data into the GOM software, and through the common point alignment instruction, cover the partial model data with the standard model data to obtain the complete model data corresponding to the partial model data.

[0041] According to one aspect of the above technical solution, the marking module specifically includes:

[0042] A marking unit, used for spraying a developer on the surface of the dummy and marking the dummy by attaching a plurality of feature points at intervals;

[0043] The scanning unit is used to place the dummy under preset environmental conditions and perform a comprehensive multi-directional scan on the dummy to obtain a plurality of image data containing all the feature points.

[0044] According to one aspect of the above technical solution, the second data module is specifically used to: scan a number of target image data of the dummy in the target environment, and splice the several target image data based on the common identifiable feature points in the target image data to obtain partial model data of the dummy. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 This is a flow chart of a method for collecting dummy data in a first embodiment of the present invention;

[0046] Figure 2 It is a structural block diagram of a method for collecting dummy data in a second embodiment of the present invention;

[0047] Description of main component symbols:

[0048] Tagging Module 100 First data module 200 Second data module 300 Processing Module 400 Measurement module 500

[0049] The following specific implementation manner will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0050] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Several embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0051] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.

[0052] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0053] See also Figure 1 , which is a flow chart of a method for collecting dummy data in a first embodiment of the present invention, comprising the following steps:

[0054] Step S100 , marking a plurality of feature points on the dummy, and acquiring a plurality of image data of the dummy in multiple directions by scanning, each of the image data including a plurality of the feature points arranged at intervals.

[0055] Preferably, in this embodiment, the above step S100 specifically includes:

[0056] Step S110, spraying a developer on the surface of the dummy, and marking the dummy with a plurality of feature points at intervals;

[0057] Step S120, the dummy is placed under preset environmental conditions, and the dummy is scanned in all directions to obtain multiple image data containing all the feature points. In some application scenarios of this embodiment, the developer is first sprayed on the dummy, and then small dots are pasted on the surface of the dummy, which is the information source for subsequent three-dimensional imaging acquisition instrument recognition, that is, the above-mentioned feature points. This step is mainly to convert the complete solid surface image data into a number of separate feature points, which is convenient for subsequent three-dimensional imaging data processing. The main purpose of this step is to obtain the complete standard model data of the dummy. The above-mentioned preset environmental conditions, that is, a wide and bright environment, are convenient for collecting the overall appearance of the dummy including the collection of subtle features relative to the in-car environment, so as to ensure that the complete standard model data is obtained. In addition, in this step, there is no special requirement for the location of the above-mentioned small dots, but in order to be effective in the subsequent data processing, it is necessary to control the distance between every two adjacent feature points to be within the preset range, and every three adjacent feature points to be on non-same straight lines (to facilitate the formation of a surface based on each point). Preferably, in some application scenarios of this embodiment, the above-mentioned preset range is 4cm-6cm, and the distance between each small dot is preferably 5cm in this embodiment.

[0058] Step S200, based on the common feature points in each of the image data, a plurality of the image data are spliced ​​to obtain the standard model data of the dummy. Preferably, in this embodiment, the above step S200 specifically includes:

[0059] Step S210, constructing and processing the feature points in each of the image data in turn to obtain a plurality of visualized feature surface data;

[0060] Step S220, based on the common feature points in the feature surface data, each of the feature surfaces is spliced ​​to obtain the standard model data of the dummy.

[0061] Step S300 , obtaining a plurality of identifiable feature points of the dummy in the target environment by scanning, so as to obtain partial model data of the dummy.

[0062] Preferably, in this embodiment, the above step S300 specifically includes:

[0063] Step S310, by scanning a plurality of target image data of the dummy in the target environment, and based on the common identifiable feature points in the target image data, the plurality of target image data are spliced ​​to obtain partial model data of the dummy. In this step, the plurality of target image data, i.e., images obtained when the dummy is in the cab or the back seat of the vehicle, and the identifiable feature points, i.e., part of the feature points, cannot be identified because the dummy partially fits the seat and the space in the vehicle is limited, i.e., the feature points in the acquired image are missing, resulting in only incomplete partial model data. In the prior art, the H point data is estimated by the incomplete partial model data, and the estimated H point data is used in the subsequent data analysis.

[0064] For ease of understanding, the dummy's H-point data, i.e., the midpoints of the connection points between the two sides of the dummy's torso and the two thighs, will change accordingly due to different environments, such as the cab or rear seat of the same vehicle, or in different vehicles. The above-mentioned target environment is the corresponding position of the competing vehicle to be measured, and the above-mentioned partial model data is the feature point data that can be collected in the above-mentioned environment. To facilitate the subsequent alignment processing operation, the above-mentioned feature point data needs to be collected as much as possible. At the same time, to ensure data accuracy, it is necessary to ensure that the setting position of the small dots relative to the dummy when the standard model data is collected for the first time is unchanged from the setting position of the small dots relative to the dummy when the partial model data of the dummy is obtained in this step.

[0065] Step S400, performing alignment processing based on common feature points in the partial model data and the standard model data to obtain complete model data corresponding to the partial model data.

[0066] Specifically, in this embodiment, the above step S400 specifically includes:

[0067] Step S410, importing the partial model data and the standard model data into the GOM software, and overwriting the partial model data with the standard model data through a common point alignment instruction to obtain complete model data corresponding to the partial model data.

[0068] In addition, it should be noted that in the above step S200, the step of obtaining the standard model data of the dummy specifically includes:

[0069] The image data corresponding to each limb part of the dummy is processed separately to obtain standard model data including multiple independent limb model data. In some application scenarios of this embodiment, when acquiring the standard model data, the data collection efficiency can be improved by placing the dummy lying flat, and by processing the multiple limb model data in the standard model data separately, that is, when the dummy is subsequently placed in the target environment, even if the posture of the dummy changes, that is, when the angle of each joint limb changes, each limb data is individually aligned to obtain the complete model data of the dummy in the target environment posture.

[0070] Step S500, based on the complete model data, the H-point data of the dummy in the target environment is measured and obtained. By obtaining the complete model data in the target environment, the H-point data of the dummy in the target environment, i.e., the positioning reference point, can be accurately found, so as to facilitate the subsequent vehicle data analysis based on the positioning reference point. At the same time, the position data of other parts such as eyes and hands obtained based on the accurate H-point will be more accurate, which improves the technical support for the analysis of competing vehicles and facilitates the subsequent testing of multiple indicators. For example, by obtaining the eye position data of the dummy in the car, it is convenient to obtain the relevant field of view data of the driver or passenger in the car.

[0071] In summary, the dummy data collection method in this embodiment marks multiple feature points on the dummy, and obtains multiple image data of the dummy in multiple directions by scanning. The main purpose of scanning and obtaining the above image data is to collect the above feature points, which is equivalent to converting the complete solid surface image data into a number of separate feature points, and further splicing the multiple image data based on the common feature points in the image data to obtain the complete standard model data of the dummy, and then put the dummy into the target driving position environment. Since the dummy is in a specific target environment, some data is difficult to collect. The corresponding target image data is obtained by scanning the dummy, and then the partial model data of the dummy is obtained. Then, the standard model data obtained before is used, and alignment processing is performed based on the common feature points in the partial model data and the standard model data, so as to obtain the complete model data corresponding to the partial model data, that is, the complete model data of the dummy in the target environment, breaking through the constraints of the environment, and then measuring the H-point data of the dummy in the target environment, which greatly improves the technical reference value of visualization data for newly developed products and improves the technical support for the analysis of competing vehicles. At the same time, as long as the feature points on the dummy remain unchanged, the above-mentioned standard model data can be saved and reused, and the relevant model data of the same dummy in different scenarios can be improved to obtain accurate actual H-point data, thereby improving data collection and analysis efficiency.

[0072] like Figure 2As shown, the second embodiment of the present invention provides a dummy data collection system, comprising:

[0073] The marking module 100 is used to mark a plurality of feature points on the dummy, and obtain a plurality of image data of the dummy in multiple directions by scanning, each of which includes a plurality of feature points arranged at intervals;

[0074] The first data module 200 is used to perform splicing processing on the plurality of image data based on the common feature points in each of the image data to obtain the standard model data of the dummy;

[0075] The second data module 300 is used to obtain a number of identifiable feature points of the dummy in the target environment by scanning, so as to obtain partial model data of the dummy;

[0076] A processing module 400 is used to perform alignment processing based on common feature points in the partial model data and the standard model data to obtain complete model data corresponding to the partial model data;

[0077] The measuring module 500 is used to measure and obtain the H-point data of the dummy in the target environment based on the complete model data.

[0078] Preferably, in this embodiment, the processing module 400 specifically includes:

[0079] A processing unit constructs and processes the feature points in each of the image data in turn to obtain a plurality of visualized feature surface data;

[0080] The splicing unit splices each of the feature surfaces based on the common feature points in the feature surface data to obtain the standard model data of the dummy.

[0081] Preferably, in this embodiment, the marking module 100 is further used to: control the distance between every two adjacent feature points to be within a preset range, and control every three adjacent feature points to be on non-coordinated lines.

[0082] Preferably, in this embodiment, the first data module 200 is further used for:

[0083] The image data corresponding to each limb part of the dummy are processed separately to obtain standard model data including a plurality of independent limb model data.

[0084] Preferably, in this embodiment, the above-mentioned second data module 300 is also used to: import the partial model data and the standard model data into the GOM software, and through the common point alignment instruction, overwrite the partial model data with the standard model data to obtain the complete model data corresponding to the partial model data.

[0085] Preferably, in this embodiment, the marking module 100 specifically includes:

[0086] A marking unit, used for spraying a developer on the surface of the dummy and marking the dummy by attaching a plurality of feature points at intervals;

[0087] The scanning unit is used to place the dummy under preset environmental conditions and perform a comprehensive multi-directional scan on the dummy to obtain a plurality of image data containing all the feature points.

[0088] Preferably, in this embodiment, the above-mentioned second data module 300 is specifically used for: scanning a plurality of target image data of the dummy in the target environment, and splicing the plurality of target image data based on the common identifiable feature points in the target image data to obtain partial model data of the dummy.

[0089] In summary, the dummy data acquisition system in this embodiment first marks multiple feature points on the dummy through the marking module 100, and obtains multiple image data of the dummy in multiple directions through scanning. The main purpose of scanning and obtaining the above-mentioned image data is to collect the above-mentioned feature points, which is equivalent to converting the complete solid surface image data into a number of separate feature points, and further splicing the multiple image data based on the common feature points in the image data through the first data module 200 to obtain the complete standard model data of the dummy, and then put the dummy into the environment of the target driving position. Since the dummy is in a specific target environment, some data is difficult to collect, and the dummy is scanned by the second data module 300 to obtain the corresponding target image data, and then the partial model data of the dummy is obtained. The model data is then obtained by processing the module 400 and utilizing the previously acquired standard model data, and alignment processing is performed based on the common feature points in the partial model data and the standard model data, so as to obtain the complete model data corresponding to the partial model data, that is, the complete model data of the dummy in the target environment, breaking through the environmental constraints, and then obtaining the H-point data of the dummy in the target environment through the measurement module 500, which greatly improves the technical reference value of the visualization data for the newly developed products and the technical support for the analysis of competing vehicles. At the same time, as long as the feature points on the dummy remain unchanged, the above-mentioned standard model data can be saved and reused, and the relevant model data of the same dummy in different scenarios can be improved to obtain accurate actual H-point data, thereby improving the efficiency of data collection and analysis.

[0090] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0091] The above-described embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the present invention. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the attached claims.

Claims

1. A method for collecting dummy data, characterized in that: The following steps are involved: Marking a plurality of characteristic points on the dummy, and acquiring a plurality of image data of the dummy in multiple directions by scanning, each of the image data including a plurality of the characteristic points arranged at intervals; Based on the common feature points in each of the image data, a plurality of the image data are spliced ​​to obtain standard model data of the dummy; Obtaining a number of identifiable feature points of the dummy in the target environment by scanning, so as to obtain partial model data of the dummy; Performing alignment processing based on common feature points in the partial model data and the standard model data to obtain complete model data corresponding to the partial model data; The H-point data of the dummy in the target environment is measured based on the complete model data.

2. The method for collecting dummy data according to claim 1, characterized in that: The step of performing splicing processing on the plurality of image data based on the common feature points in each of the image data to obtain the standard model data of the dummy specifically includes: Sequentially constructing and processing the feature points in each of the image data to obtain a plurality of visualized feature surface data; Based on the common feature points in the feature surface data, each feature surface is spliced ​​to obtain the standard model data of the dummy.

3. The method for collecting dummy data according to claim 1, characterized in that: In the step of marking a plurality of feature points on the dummy, the method further comprises: The distance between every two adjacent feature points is controlled to be within a preset range, and every three adjacent feature points are not on the same straight line.

4. The method for collecting dummy data according to claim 1 or 2, characterized in that: The step of obtaining the standard model data of the dummy specifically includes: The image data corresponding to each limb part of the dummy are processed separately to obtain standard model data including a plurality of independent limb model data.

5. The method for collecting dummy data according to claim 1, characterized in that: The step of aligning the partial model data and the standard model data based on the identifiable feature points to obtain the complete model data corresponding to the partial model data specifically includes: The partial model data and the standard model data are imported into the GOM software, and the standard model data is used to overwrite the partial model data through a common point alignment instruction to obtain complete model data corresponding to the partial model data.

6. The method for collecting dummy data according to claim 1, characterized in that: The steps of marking multiple feature points on the dummy and acquiring multiple image data of the dummy in multiple directions by scanning specifically include: The surface of the dummy is sprayed with a developer, and a plurality of feature points are attached at intervals to mark the dummy; The dummy is placed under preset environmental conditions, and the dummy is fully scanned in multiple directions to obtain a plurality of image data containing all the feature points.

7. The method for collecting dummy data according to claim 1, characterized in that: The step of obtaining a plurality of identifiable feature points of the dummy in the target environment by scanning to obtain partial model data of the dummy specifically includes: Partial model data of the dummy is obtained by scanning a plurality of target image data of the dummy in the target environment and splicing the plurality of target image data based on common identifiable feature points in the target image data.

8. A dummy data collection system, characterized in that: include: A marking module, used for marking a plurality of characteristic points on the dummy, and obtaining a plurality of image data of the dummy in multiple directions by scanning, each of the image data including a plurality of the characteristic points arranged at intervals; A first data module, used for performing splicing processing on a plurality of the image data based on common feature points in each of the image data to obtain standard model data of the dummy; A second data module is used to obtain a number of identifiable feature points of the dummy in the target environment by scanning, so as to obtain partial model data of the dummy; A processing module, configured to perform alignment processing based on common feature points in the partial model data and the standard model data to obtain complete model data corresponding to the partial model data; A measuring module is used to measure and obtain H-point data of the dummy in the target environment based on the complete model data.

9. The dummy data collection system according to claim 8, characterized in that: The processing module specifically includes: A processing unit constructs and processes the feature points in each of the image data in turn to obtain a plurality of visualized feature surface data; The splicing unit splices each of the feature surfaces based on the common feature points in the feature surface data to obtain the standard model data of the dummy.

10. The dummy data collection system according to claim 8, characterized in that: The marking module is further used to control the distance between every two adjacent feature points to be within a preset range, and every three adjacent feature points to be on non-coordinate lines.

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