Digital virtual human naked eye 3D display method and system

Abstract

The invention relates to the technical field of naked-eye 3D display, in particular to a naked-eye 3D display method and system for a digital virtual human. The method comprises the following steps: acquiring geometric structures of parts by acquiring design data of mechanical measurement parts, and performing dynamic characteristic analysis based on the geometric data; constructing an optical three-dimensional model of the mechanical measurement part according to the geometric data and the dynamic characteristic data, and acquiring multi-view data in motion through multi-view acquisition; constructing a disparity map by using the multi-view data, and generating a digital virtual naked-eye 3D display image based on the disparity map data; performing anomaly analysis on the naked-eye 3D display image, identifying problems such as display distortion, detail loss or depth dislocation, and generating naked-eye 3D abnormal data; performing optical characteristic correction on the digital virtual naked eye 3D display image according to the abnormal data; the naked eye 3D display is optimized, so that the naked eye 3D display is clearer and more stereoscopic.

Description

Technical Field

[0001] The present invention relates to the field of naked-eye 3D display technology, and in particular to a naked-eye 3D display method and system for digital virtual humans. Background Art

[0002] Mechanical measurement components are key components of precision manufacturing and measurement systems. Their geometric structure, dynamic characteristics and optical characteristics directly affect the measurement accuracy and system stability. In the process of mechanical measurement, it is particularly important to accurately restore the true shape, motion trajectory and interaction of mechanical components with the external environment. Traditional mechanical component analysis methods usually rely on two-dimensional images, CAD models and other methods, but these methods cannot fully display the details and three-dimensional information of the components, limiting the comprehensive understanding of their complex characteristics. Naked-eye 3D display technology based on multi-view image acquisition, depth perception and optical feature analysis has been gradually introduced into the field of mechanical component analysis and display. By constructing an optical three-dimensional model of the mechanical measurement component and using multi-view image data to generate a disparity map, the shape and detail information of the mechanical component at different perspectives can be accurately reproduced, achieving a more intuitive and clear naked-eye 3D display effect. However, a traditional naked-eye 3D display method for digital virtual humans has the problem of inaccurate analysis of the dynamic characteristics of mechanical measurement components and inaccurate analysis of abnormal naked-eye 3D display images. Summary of the invention

[0003] Based on this, it is necessary to provide a naked-eye 3D display method and system for digital virtual humans to solve at least one of the above technical problems.

[0004] To achieve the above purpose, a method for naked-eye 3D display of digital virtual humans comprises the following steps:

[0005] Step S1: Acquire design data of a mechanical measurement component; collect the geometric structure of the mechanical measurement component according to the design data of the mechanical measurement component to obtain geometric structure data of the mechanical measurement component; perform dynamic characteristic analysis of the mechanical measurement component based on the geometric structure data of the mechanical measurement component to obtain dynamic characteristic data of the mechanical measurement component;

[0006] Step S2: constructing an optical three-dimensional model of the mechanical measurement component based on the mechanical measurement component design data, the mechanical measurement component geometric structure data, and the mechanical measurement component dynamic characteristic data to obtain the optical three-dimensional model of the mechanical measurement component; performing multi-view acquisition of the mechanical measurement component according to the optical three-dimensional model of the mechanical measurement component to obtain multi-view motion data of the mechanical measurement component;

[0007] Step S3: constructing a parallax map of the mechanical measurement component according to the multi-view data of the mechanical measurement component movement to obtain the parallax map data of the mechanical measurement component; constructing a digital virtual naked-eye 3D display image based on the parallax map data of the mechanical measurement component to obtain the naked-eye 3D display image data of the digital virtual human;

[0008] Step S4: performing naked-eye 3D abnormality analysis of mechanical measurement components based on the naked-eye 3D display image data of the digital virtual human to obtain naked-eye 3D abnormality data of the mechanical measurement components; performing naked-eye 3D optical property correction on the digital virtual naked-eye 3D display image data according to the naked-eye 3D abnormality data of the mechanical measurement components to obtain naked-eye 3D optical property correction data.

[0009] The present invention can comprehensively reflect the complex characteristics of mechanical measurement components by accurately collecting and analyzing the design data, geometric structure data and dynamic characteristic data of mechanical measurement components. By obtaining the design data of mechanical measurement components and performing geometric structure collection, the geometric form of mechanical components can be obtained efficiently and accurately, which provides a solid foundation for subsequent modeling and analysis. On this basis, dynamic characteristic analysis based on geometric structure data can deeply understand the motion behavior and mechanical response of components in dynamic environments, and provide key information for the evaluation of system stability and accuracy. By constructing an optical three-dimensional model based on the geometric structure data and dynamic characteristic data of mechanical measurement components, a three-dimensional virtual model with higher accuracy and sense of reality can be generated, making the visual effect of the component more realistic and credible. Through multi-view data collection, the parallax information of the mechanical measurement component at different angles can be further obtained, which can provide the necessary depth information for the realization of naked-eye 3D display. The generation of the parallax map can accurately restore the three-dimensional structure and depth information of the component through the processing of multi-view data, and provide accurate parallax data support for naked-eye 3D display. After using the disparity map data for detail rendering, the system can better display the stereoscopic sense and detail effects of the mechanical measurement components in the naked eye 3D display, so that users can more intuitively observe the morphological changes and complex details of the mechanical components at different angles. This optimization of detail rendering and display effect not only improves the visualization effect of the mechanical components, but also provides effective support for more accurate measurement and analysis. In addition, by using the naked eye 3D abnormality analysis and optical property correction function, image distortion is further eliminated during the display process, the accuracy and reliability of the displayed image are improved, and the actual characteristics of the mechanical components are accurately and correctly presented in the naked eye 3D display. Through the precise adjustment of the optical property correction, the problem of detail loss caused by display distortion is eliminated, and the realism and operability of the displayed image are further enhanced. Therefore, the present invention is an optimization process made to the traditional naked eye 3D display method of digital virtual human, which solves the problem of inaccurate analysis of the dynamic characteristics of mechanical measurement components and inaccurate analysis of abnormalities of naked eye 3D display images in a traditional naked eye 3D display method of digital virtual human. The accuracy of the dynamic characteristics analysis of mechanical measurement components and the accuracy of the abnormal analysis of naked eye 3D display images are improved.

[0010] Preferably, step S1 comprises the following steps:

[0011] Step S11: Acquire mechanical measurement component design data;

[0012] Step S12: collecting the geometric structure of the mechanical measurement component according to the design data of the mechanical measurement component to obtain the geometric structure data of the mechanical measurement component;

[0013] Step S13: performing stability analysis on the mechanical measurement component based on the geometric structure data of the mechanical measurement component and the design data of the mechanical measurement component to obtain stability data of the mechanical measurement component;

[0014] Step S14: performing a dynamic characteristic analysis of the mechanical measurement component based on the stability data of the mechanical measurement component and the geometric structure data of the mechanical measurement component to obtain the dynamic characteristic data of the mechanical measurement component.

[0015] The present invention can accurately analyze and obtain the multi-dimensional characteristics of mechanical components through comprehensive processing of mechanical measurement component design data and geometric structure data. After obtaining the design data, the geometric structure of the component is collected, which can provide necessary geometric information for subsequent analysis and modeling, and ensure the accuracy and completeness of the data. Stability analysis is performed through geometric structure data and design data, and the stability characteristics of the components such as compression resistance and bending resistance in actual use are deeply evaluated, providing a scientific basis for mechanical design and safety verification. In addition, the dynamic characteristic analysis based on stability data and geometric structure data can not only reveal the motion response of the components in a dynamic environment, but also effectively predict the performance under different working conditions, helping to improve the performance and accuracy of the components. The combination of these steps ensures the all-round optimization of the components during design, manufacturing and use, improves the accuracy and reliability of mechanical measurement, and provides a solid data foundation for subsequent three-dimensional modeling and display.

[0016] Preferably, step S13 comprises the following steps:

[0017] Step S131: collecting the material of the mechanical measurement component according to the mechanical measurement component design data to obtain the material data of the mechanical measurement component;

[0018] Step S132: Calculate the material strength of the mechanical measurement component according to the material data of the mechanical measurement component to obtain the material strength data of the mechanical measurement component;

[0019] Step S133: Calculate the arc of the measuring point of the mechanical measuring component according to the geometric structure data of the mechanical measuring component to obtain the arc data of the measuring point of the mechanical measuring component;

[0020] Step S134: performing bending stiffness analysis of the mechanical measurement component based on the arc data of the mechanical measurement component measurement point and the material strength data of the mechanical measurement component to obtain bending stiffness data of the mechanical measurement component;

[0021] Step S135: Predicting the stress and deformation of the mechanical measurement component bending stiffness data and the arc data of the mechanical measurement component measurement point to obtain stress and deformation data of the measurement component;

[0022] Step S137: performing stability analysis on the mechanical measurement component according to the bending stiffness data of the mechanical measurement component and the force deformation data of the measurement component to obtain stability data of the mechanical measurement component.

[0023] The present invention can comprehensively evaluate the mechanical properties and stability of components through comprehensive analysis of various data such as the material, geometric structure and force characteristics of mechanical measurement components, obtain component material information from design data, and provide an accurate physical basis for subsequent strength calculation and mechanical analysis. Through the calculation of material strength, the durability and resistance of the component in actual use are obtained to ensure that it can operate safely under various working conditions. Calculating the radian of the measuring point in combination with the geometric structure data is helpful to accurately analyze the shape and force changes of the component, and then provide data support for the bending stiffness analysis, and evaluate the deformation of the component under the action of external force. Based on the bending stiffness data and the radian data of the measuring point, the force deformation is estimated, and the deformation of the component during use is accurately predicted, thereby providing a data basis for design optimization. Through the comprehensive analysis of the bending stiffness and deformation data, the component stability data obtained can effectively evaluate its stability and reliability in actual application, and provide scientific support for the safety design and optimization of mechanical components.

[0024] Preferably, step S14 comprises the following steps:

[0025] Step S141: collecting the motion trajectory of the mechanical measurement component according to the geometric structure data of the mechanical measurement component to obtain the motion trajectory data of the mechanical measurement component;

[0026] Step S142: measuring the clearance of the sliding axis of the mechanical measuring component according to the geometric structure data of the mechanical measuring component and the motion trajectory data of the mechanical measuring component to obtain the clearance data of the sliding axis of the mechanical measuring component;

[0027] Step S143: Calculating the friction coefficient of the mechanical measurement component based on the mechanical measurement component sliding axis point clearance data and the mechanical measurement component design data to obtain the mechanical measurement component friction coefficient data;

[0028] Step S144: estimating the sliding smoothness of the measuring component according to the friction coefficient data of the mechanical measuring component and the stability data of the mechanical measuring component to obtain the sliding smoothness data of the measuring component;

[0029] Step S145: Calculate the influence of the measuring component accuracy according to the measuring component sliding smoothness data, the mechanical measuring component stability data and the mechanical measuring component friction coefficient data to obtain the measuring component accuracy influence data;

[0030] Step S146: Performing a dynamic characteristic analysis of the mechanical measuring component based on the measuring component accuracy influence data and the measuring component sliding smoothness data to obtain the mechanical measuring component dynamic characteristic data.

[0031] The present invention can comprehensively evaluate the motion performance and precision influence of the components by systematically analyzing the geometric structure, motion trajectory, friction characteristics and other factors of the mechanical measurement components. By combining the motion trajectory acquisition and geometric structure data, basic data is provided for the subsequent sliding axis point gap measurement, which can accurately reflect the geometric deformation and contact gap changes in the movement of the components. This process is crucial to ensure the accuracy of the components and reduce friction and wear during the movement. Further calculation of the friction coefficient provides a quantitative basis for the friction force of the components in actual operation, which helps to optimize the design, reduce energy loss and improve movement efficiency. Combining stability data to estimate the sliding smoothness, predict the stability of the components during use, and avoid abnormal operation caused by unstable factors. By comprehensively considering the sliding smoothness, friction coefficient and stability, the data affecting the accuracy of the components is calculated, which helps to fully understand how these factors work together on the measurement accuracy, improve product quality and accuracy, and through dynamic characteristic analysis, the motion characteristics of the mechanical measurement components can be optimized at the system level to ensure their stability and efficiency under various working conditions, and significantly improve the performance and reliability of the mechanical measurement system.

[0032] Preferably, step S2 comprises the following steps:

[0033] Step S21: performing optical characteristic analysis of the mechanical measurement component according to the mechanical measurement component design data to obtain optical characteristic data of the mechanical measurement component;

[0034] Step S22: constructing an optical three-dimensional model of the mechanical measurement component based on the optical characteristic data of the mechanical measurement component, the geometric structure data of the mechanical measurement component, and the dynamic characteristic data of the mechanical measurement component to obtain an optical three-dimensional model of the mechanical measurement component;

[0035] Step S23: performing multi-level resolution segmentation according to the three-dimensional model of the mechanical measurement component to obtain multi-level resolution segmentation data of the three-dimensional model;

[0036] Step S24: performing multi-view acquisition of the mechanical measurement component according to the multi-level resolution segmentation data of the three-dimensional model to obtain multi-view data of the movement of the mechanical measurement component.

[0037] The present invention obtains key information such as component surface material, reflectivity, glossiness, etc. by analyzing the optical characteristics of the design data of the mechanical measurement component, which is crucial for the construction of the subsequent optical model. These optical characteristic data are combined with geometric structure and dynamic characteristic data to build an accurate optical three-dimensional model of the mechanical measurement component, ensuring that the model can truly reflect the geometric shape and optical behavior of the component, thereby improving the accuracy and realism of the display effect. On this basis, by performing multi-level resolution segmentation on the three-dimensional model, it is helpful to optimize the processing and display of the model at different levels of detail, and improve the rendering efficiency and performance of the system. Resolution segmentation can also select different levels of details according to needs, reduce the amount of calculation and improve the real-time performance of the display effect. Combined with multi-view acquisition technology, it can fully obtain multi-angle data of the component, provide sufficient viewing angle information for subsequent naked-eye 3D display image generation, ensure the richness and three-dimensionality of the visual effect, enable the naked-eye 3D display technology of digital virtual people to be realized, and enhance the user's immersion and interactive experience.

[0038] Preferably, step S21 includes the following steps:

[0039] Step S211: performing physical property detection of the mechanical measurement component on the mechanical measurement component design data to obtain physical property data of the mechanical measurement component;

[0040] Step S212: performing surface roughness detection of the mechanical measurement component according to the physical property data of the mechanical measurement component to obtain surface roughness data of the mechanical measurement component;

[0041] Step S213: performing texture feature analysis of the mechanical measurement component based on the surface roughness data of the mechanical measurement component to obtain texture feature data of the mechanical measurement component;

[0042] Step S214: calculating the component surface reflectivity according to the mechanical measurement component texture feature data and the mechanical measurement component surface roughness data to obtain the component surface reflectivity data;

[0043] Step S215: Analyze the visual effect of the component based on the component surface reflectivity data and the mechanical measurement component texture feature data to obtain the mechanical measurement component visual effect data;

[0044] Step S216: performing optical characteristic analysis of the mechanical measurement component according to the visual effect data of the mechanical measurement component and the component surface reflectivity data to obtain the optical characteristic data of the mechanical measurement component.

[0045] The present invention conducts physical property detection on the design data of mechanical measurement components to deeply understand the basic material properties of the components, such as density, hardness, etc., which provides the necessary basic information for the subsequent surface roughness and optical property analysis. Then, the surface roughness detection helps to accurately capture the details of the microstructure of the component surface, and further reveals the influence of surface characteristics on light reflection. Based on these surface roughness data, texture feature analysis can identify and quantify the pattern of component surface texture, such as bumps, scratches, etc., and then predict the propagation mode of light on the surface. This process provides data support for calculating the reflectivity of the component surface, so that the surface reflection effect under illumination can be accurately evaluated to ensure that the real optical behavior is reflected in the optical model. Combined with texture features and reflectivity data, the visual effect analysis of the component can evaluate the influence of different materials and surface treatment methods on visual perception, and provide optimization direction for subsequent image rendering and virtual reality display. By integrating visual effects and reflectivity data, the optical feature analysis of mechanical measurement components can provide accurate data support for the construction of optical three-dimensional models, thereby improving the authenticity and immersion of naked-eye 3D display.

[0046] Preferably, step S3 comprises the following steps:

[0047] Step S31: constructing a disparity map of the mechanical measurement component according to the multi-view data of the movement of the mechanical measurement component to obtain disparity map data of the mechanical measurement component;

[0048] Step S32: performing detail rendering adjustment based on the mechanical measurement component disparity map data to obtain mechanical measurement component detail rendering data;

[0049] Step S33: constructing a digital virtual naked-eye 3D display image based on the mechanical measurement component detail rendering data and the mechanical measurement component parallax map data to obtain digital virtual human naked-eye 3D display image data.

[0050] The present invention constructs a disparity map based on multi-view data of the movement of mechanical measurement components, which can effectively extract the spatial differences and depth information of components under different viewing angles, and provide accurate depth mapping data for subsequent naked-eye 3D display. This step can ensure the authenticity of the stereoscopic effect, especially in the dynamic changes of complex components, and accurately capture each detail. Then, based on the disparity map data, detail rendering adjustments are made to optimize the visual effect of the image, enhance the surface texture, glossiness and true expression of tiny details of the components, thereby reducing visual distortion, increasing the layering and immersion of the image, and constructing a digital virtual naked-eye 3D display image through detail rendering data and disparity map data, which can present a three-dimensional stereoscopic visual effect to the user without wearing glasses. This method not only improves the depth perception of the image, but also improves the clarity and visual comfort of the display, and is particularly suitable for high-precision mechanical measurement and display.

[0051] Preferably, step S31 includes the following steps:

[0052] Step S311: collecting a stereo image pair according to the multi-view data of the movement of the mechanical measurement component to obtain the stereo image pair data of the mechanical measurement component;

[0053] Step S312: performing image grayscale processing on the stereo image pair data of the mechanical measurement component to obtain stereo image pair image grayscale data;

[0054] Step S313: calculating the disparity value of the image pair based on the grayscale data of the stereo image pair to obtain the disparity value data of the stereo image pair;

[0055] Step S314: performing grayscale image mapping on the image disparity value data according to the stereo image to obtain disparity value grayscale image mapping data;

[0056] Step S315: constructing a mechanical measurement component disparity map based on the disparity value grayscale image mapping data and the stereo image disparity value data to obtain mechanical measurement component disparity map data.

[0057] The present invention acquires stereoscopic image pairs according to multi-view data of the movement of mechanical measurement components to obtain detailed visual information of the components from different viewpoints, thereby providing accurate depth and spatial information for subsequent three-dimensional modeling. The image grayscale processing converts the detailed information of the image into grayscale data, so that the contrast and clarity of the image are more prominent, which is convenient for extracting more accurate depth information in subsequent steps. Next, the image disparity value is calculated based on the grayscale data, and the depth difference between the images can be further extracted, which provides basic depth mapping data for the construction of naked-eye 3D images. Through grayscale image mapping, the disparity value can be converted into a grayscale image, and the depth effect can be further refined and optimized, so that the image at different distances is more natural. Based on these data, the disparity map of the mechanical measurement component is constructed to provide depth information support for the naked-eye 3D display image, thereby ensuring the stereoscopic sense and detail display of the image, so that the mechanical components present a more realistic and clear three-dimensional effect when displayed.

[0058] Preferably, step S4 comprises the following steps:

[0059] Step S41: estimating the distortion status of naked-eye 3D display based on the naked-eye 3D display image data of the digital virtual human to obtain the distortion status data of the naked-eye 3D display;

[0060] Step S42: performing mechanical component detail loss detection based on naked-eye 3D display distortion status data to obtain naked-eye 3D detail loss data of mechanical measurement components;

[0061] Step S43: performing naked-eye 3D abnormality analysis on the mechanical measuring component according to the naked-eye 3D detail loss data and the naked-eye 3D display distortion status data of the mechanical measuring component to obtain naked-eye 3D abnormality data of the mechanical measuring component;

[0062] Step S44: performing naked-eye 3D optical characteristic correction on the digital virtual naked-eye 3D display image data according to the naked-eye 3D abnormal data of the mechanical measurement component to obtain naked-eye 3D optical characteristic correction data.

[0063] The present invention estimates the distortion of naked-eye 3D display based on the digital virtual human naked-eye 3D display image data, identifies and predicts the distortion problems in the displayed image in advance, which helps to optimize the naked-eye 3D effect and improve the realism of the displayed image. Further, based on the distortion status data, the mechanical parts detail loss detection is performed to accurately detect which parts of the 3D display have lost details, thereby ensuring the integrity of the display effect. Combining the detail loss data with the distortion status, naked-eye 3D abnormality analysis is performed, which helps to comprehensively evaluate and locate the problem areas in the display process, ensure the high-quality presentation of the digital virtual naked-eye 3D image, and correct the optical characteristics of the displayed image based on the naked-eye 3D abnormality data obtained by analysis, effectively adjust the color, brightness and depth performance of the image, and eliminate the optical deviation that occurs during the display process, thereby achieving a clearer and more accurate naked-eye 3D display effect and enhancing the audience's visual experience.

[0064] The present invention also provides a digital virtual human naked eye 3D display system, which is used to execute the digital virtual human naked eye 3D display method as described above, and the digital virtual human naked eye 3D display system comprises:

[0065] A dynamic characteristic analysis module is used to obtain the design data of the mechanical measurement component; collect the geometric structure of the mechanical measurement component according to the design data of the mechanical measurement component to obtain the geometric structure data of the mechanical measurement component; and analyze the dynamic characteristics of the mechanical measurement component based on the geometric structure data of the mechanical measurement component to obtain the dynamic characteristics data of the mechanical measurement component;

[0066] A component multi-view acquisition module is used to construct an optical three-dimensional model of a mechanical measurement component based on the mechanical measurement component design data, the mechanical measurement component geometric structure data, and the mechanical measurement component dynamic characteristic data to obtain an optical three-dimensional model of the mechanical measurement component; perform multi-view acquisition of the mechanical measurement component based on the optical three-dimensional model of the mechanical measurement component to obtain multi-view motion data of the mechanical measurement component;

[0067] A naked-eye 3D display image construction module is used to construct a parallax map of a mechanical measurement component according to the multi-view data of the movement of the mechanical measurement component to obtain the parallax map data of the mechanical measurement component; and to construct a digital virtual naked-eye 3D display image based on the parallax map data of the mechanical measurement component to obtain the naked-eye 3D display image data of a digital virtual human;

[0068] The naked-eye 3D optical property correction module is used to perform naked-eye 3D anomaly analysis of mechanical measurement components based on naked-eye 3D display image data of digital virtual humans to obtain naked-eye 3D anomaly data of mechanical measurement components; and perform naked-eye 3D optical property correction on digital virtual naked-eye 3D display image data according to naked-eye 3D anomaly data of mechanical measurement components to obtain naked-eye 3D optical property correction data.

[0069] The present invention is that by accurately collecting and analyzing the design data, geometric structure data and dynamic characteristic data of the mechanical measurement component, the complex characteristics of the mechanical measurement component can be fully reflected. By obtaining the design data of the mechanical measurement component and performing geometric structure collection, the geometric shape of the mechanical component can be obtained efficiently and accurately, which provides a solid foundation for subsequent modeling and analysis. On this basis, dynamic characteristic analysis based on geometric structure data can deeply understand the motion behavior and mechanical response of the component in a dynamic environment, and provide key information for the evaluation of system stability and accuracy. By constructing an optical three-dimensional model based on the geometric structure data and dynamic characteristic data of the mechanical measurement component, a three-dimensional virtual model with higher accuracy and sense of reality can be generated, making the visual effect of the component more realistic and credible. Through multi-view data collection, the parallax information of the mechanical measurement component at different angles can be further obtained, which can provide necessary depth information for the realization of naked-eye 3D display. The generation of the parallax map can accurately restore the three-dimensional structure and depth information of the component through the processing of multi-view data, and provide accurate parallax data support for naked-eye 3D display. After using the disparity map data for detail rendering, the system can better display the stereoscopic sense and detail effects of the mechanical measurement components in the naked eye 3D display, so that users can more intuitively observe the morphological changes and complex details of the mechanical components at different angles. This optimization of detail rendering and display effect not only improves the visualization effect of the mechanical components, but also provides effective support for more accurate measurement and analysis. In addition, by using the naked eye 3D abnormality analysis and optical property correction function, image distortion is further eliminated during the display process, the accuracy and reliability of the displayed image are improved, and the actual characteristics of the mechanical components are accurately and correctly presented in the naked eye 3D display. Through the precise adjustment of the optical property correction, the problem of detail loss caused by display distortion is eliminated, and the realism and operability of the displayed image are further enhanced. Therefore, the present invention is an optimization process made to the traditional naked eye 3D display method of digital virtual human, which solves the problem of inaccurate analysis of the dynamic characteristics of mechanical measurement components and inaccurate analysis of abnormalities of naked eye 3D display images in a traditional naked eye 3D display method of digital virtual human. The accuracy of the dynamic characteristics analysis of mechanical measurement components and the accuracy of the abnormal analysis of naked eye 3D display images are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 A schematic diagram of the steps of a naked-eye 3D display method for a digital virtual human;

[0071] Figure 2 for Figure 1 Detailed implementation steps of step S2 in the flowchart;

[0072] Figure 3 for Figure 1 Detailed implementation steps of step S4 in FIG.

[0073] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0074] The technical method of the present invention is described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0075] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0076] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0077] To achieve this, please refer to Figures 1 to 3 , a naked-eye 3D display method for a digital virtual human comprises the following steps:

[0078] Step S1: Acquire design data of a mechanical measurement component; collect the geometric structure of the mechanical measurement component according to the design data of the mechanical measurement component to obtain geometric structure data of the mechanical measurement component; perform dynamic characteristic analysis of the mechanical measurement component based on the geometric structure data of the mechanical measurement component to obtain dynamic characteristic data of the mechanical measurement component;

[0079] Step S2: constructing an optical three-dimensional model of the mechanical measurement component based on the mechanical measurement component design data, the mechanical measurement component geometric structure data, and the mechanical measurement component dynamic characteristic data to obtain the optical three-dimensional model of the mechanical measurement component; performing multi-view acquisition of the mechanical measurement component according to the optical three-dimensional model of the mechanical measurement component to obtain multi-view motion data of the mechanical measurement component;

[0080] Step S3: constructing a parallax map of the mechanical measurement component according to the multi-view data of the mechanical measurement component movement to obtain the parallax map data of the mechanical measurement component; constructing a digital virtual naked-eye 3D display image based on the parallax map data of the mechanical measurement component to obtain the naked-eye 3D display image data of the digital virtual human;

[0081] Step S4: performing naked-eye 3D abnormality analysis of mechanical measurement components based on the naked-eye 3D display image data of the digital virtual human to obtain naked-eye 3D abnormality data of the mechanical measurement components; performing naked-eye 3D optical property correction on the digital virtual naked-eye 3D display image data according to the naked-eye 3D abnormality data of the mechanical measurement components to obtain naked-eye 3D optical property correction data.

[0082] In the embodiment of the present invention, reference Figure 1 As shown, in this example, the method for displaying a digital virtual human in naked-eye 3D includes the following steps:

[0083] Step S1: Acquire design data of a mechanical measurement component; collect the geometric structure of the mechanical measurement component according to the design data of the mechanical measurement component to obtain geometric structure data of the mechanical measurement component; perform dynamic characteristic analysis of the mechanical measurement component based on the geometric structure data of the mechanical measurement component to obtain dynamic characteristic data of the mechanical measurement component;

[0084] In an embodiment of the present invention, the design data of the mechanical measurement component is obtained by a computer-aided design (CAD) system. The design data generally includes information such as the size, shape, material, structure, etc. of the component, and is generally saved in standard CAD formats such as STEP, IGES, etc. After obtaining the design data, the next step is to perform geometric structure acquisition. The appearance of the mechanical measurement component is scanned by a high-precision three-dimensional scanning device (such as a laser scanner or a structured light scanner) to generate point cloud data or a three-dimensional mesh model, thereby obtaining the geometric structure data of the component. For complex component shapes, the point cloud data needs to be reconstructed and optimized by software to ensure the high accuracy and integrity of the geometric data. After obtaining the geometric structure data of the mechanical measurement component, dynamic characteristics analysis is performed. The analysis generally adopts a finite element analysis (FEA) method, uses a dedicated dynamics simulation software (such as ANSYS, Abaqus, etc.), and performs mechanical analysis by inputting geometric structure data and combining the physical properties of the component (such as elastic modulus, density, etc.). Through this analysis, dynamic data such as the natural frequency, vibration mode, and response characteristics of the mechanical measurement component are obtained.

[0085] Step S2: constructing an optical three-dimensional model of the mechanical measurement component based on the mechanical measurement component design data, the mechanical measurement component geometric structure data, and the mechanical measurement component dynamic characteristic data to obtain the optical three-dimensional model of the mechanical measurement component; performing multi-view acquisition of the mechanical measurement component according to the optical three-dimensional model of the mechanical measurement component to obtain multi-view motion data of the mechanical measurement component;

[0086] In an embodiment of the present invention, the design data, geometric structure data and dynamic characteristic data of the mechanical measurement component are used to construct an optical three-dimensional model through computer graphics and three-dimensional modeling software (such as Blender, 3ds Max, etc.). The model not only needs to accurately reflect the geometric shape of the component, but also should take into account physical properties such as surface smoothness, reflection characteristics, etc., especially in high-precision applications, surface details and texture features must be accurately simulated. Based on the constructed optical three-dimensional model, multi-view acquisition is started. Use multiple high-definition cameras or high-resolution cameras to shoot the mechanical measurement component at different angles to obtain corresponding motion multi-view data. These data not only include images of components at different perspectives in space, but also need to record position information related to the movement of the component (such as rotation angle, acceleration, etc.). By synthesizing these multi-view data.

[0087] Step S3: constructing a parallax map of the mechanical measurement component according to the multi-view data of the mechanical measurement component movement to obtain the parallax map data of the mechanical measurement component; constructing a digital virtual naked-eye 3D display image based on the parallax map data of the mechanical measurement component to obtain the naked-eye 3D display image data of the digital virtual human;

[0088] In an embodiment of the present invention, the multi-view data of the mechanical measurement component obtained is used to construct a disparity map. This process requires the use of a stereoscopic vision algorithm (such as a disparity matching algorithm) to compare the multi-view images and calculate the disparity value of each pixel. Specifically, each pair of pixels of the image (usually two images from adjacent perspectives) will be paired, and the disparity map is determined by calculating its position offset. During implementation, the algorithm will accurately match the texture, edge and depth information of the image to obtain the depth value of each pixel and form three-dimensional disparity map data. Based on the disparity map data, a digital virtual naked eye 3D display image is further constructed. The disparity map is converted into a 3D display image by stereo rendering technology (such as OpenGL or DirectX). This process involves adjusting the lighting, shadows, reflections and other effects of the image according to the depth information in the disparity map to ensure that the naked eye 3D image can be displayed without a sense of parallax. In this process, the rendering software needs to optimize the details of each image so that a real and stable 3D visual effect can be provided when viewed with the naked eye, and a digital virtual naked eye 3D display image data is generated.

[0089] Step S4: performing naked-eye 3D abnormality analysis of mechanical measurement components based on the naked-eye 3D display image data of the digital virtual human to obtain naked-eye 3D abnormality data of the mechanical measurement components; performing naked-eye 3D optical property correction on the digital virtual naked-eye 3D display image data according to the naked-eye 3D abnormality data of the mechanical measurement components to obtain naked-eye 3D optical property correction data.

[0090] In an embodiment of the present invention, the generated digital virtual naked-eye 3D display image data is subjected to naked-eye 3D abnormality analysis. Abnormality analysis usually uses an image quality assessment algorithm (such as structural similarity index SSIM or mean square error MSE) to compare images and detect problems such as image distortion, color deviation, depth distortion, etc. that occur during the display process. The goal of this step is to identify visual anomalies that appear in naked-eye 3D images, and to perform optical property correction on the digital virtual naked-eye 3D display image based on the naked-eye 3D abnormality data. This correction process involves optimizing the original image using an optical correction algorithm (such as an image reconstruction algorithm, a reflection correction algorithm, etc.). In operation, various factors that affect the naked-eye 3D effect are corrected one by one according to the optical property model (including parallax, reflection, refraction, etc.), especially the adjustment of the distorted part. After optical correction, the obtained naked-eye 3D image will no longer have visual abnormalities.

[0091] Preferably, step S1 comprises the following steps:

[0092] Step S11: Acquire mechanical measurement component design data;

[0093] Step S12: collecting the geometric structure of the mechanical measurement component according to the design data of the mechanical measurement component to obtain the geometric structure data of the mechanical measurement component;

[0094] Step S13: performing stability analysis on the mechanical measurement component based on the geometric structure data of the mechanical measurement component and the design data of the mechanical measurement component to obtain stability data of the mechanical measurement component;

[0095] Step S14: performing a dynamic characteristic analysis of the mechanical measurement component based on the stability data of the mechanical measurement component and the geometric structure data of the mechanical measurement component to obtain the dynamic characteristic data of the mechanical measurement component.

[0096] In an embodiment of the present invention, the design data of the mechanical measurement component is obtained from a CAD system or a design data management platform. The design data generally includes the geometric dimensions, material type, surface roughness, internal structure, load-bearing requirements, etc. of the component. These data are obtained by file import, and the file format is generally STEP, IGES or STL, etc., which are widely used in mechanical design and manufacturing. The accuracy of the design data is crucial, and it is necessary to ensure that the data extracted from the design file is not missing or wrong, so as to ensure that the analysis and modeling in the subsequent steps have sufficient accuracy. After obtaining the design data, it is necessary to conduct a preliminary inspection to confirm that the design information of all components is complete, including size, structure type, interface specification, etc., and based on the obtained mechanical measurement component design data, a high-precision three-dimensional scanning device is used to collect the geometric structure of the component. The three-dimensional scanning device can use a laser scanner or a structured light scanner, which can accurately capture the geometric shape and surface details of the component and generate three-dimensional point cloud data. For complex mechanical components, multiple scanning angles are usually used for data collection to ensure that complete geometric information is obtained. During the collection process, the scanning device needs to maintain a certain distance and angle with the measured component to ensure the accuracy of the scanning result. Then, the collected point cloud data is reconstructed by point cloud processing software to form a high-precision three-dimensional model. The model is further converted into a standard CAD model (such as STL, OBJ and other formats) and used for subsequent stability analysis and dynamic characteristics analysis. The geometric structure data needs to include information such as each surface, hole, edge and connection part of the component, and the geometric structure data and design data of the mechanical measurement component are used for stability analysis. The analysis is implemented through the finite element analysis (FEA) method. Using engineering analysis software such as ANSYS or Abaqus, the acquired geometric model is imported into the analysis software, and the corresponding boundary conditions, loading conditions (such as static load, dynamic load, etc.) and material properties are set. Through this model, the software simulates the stress and deformation of mechanical components under actual working conditions. Based on the geometric structure data of the component, the stability analysis will evaluate the response of the component under the action of external force, such as whether the component is over-deformed, whether there are potential problems such as critical fracture, etc. Especially for components with more complex structures, stability analysis will evaluate the stability of different parts to ensure that each component can withstand the expected load in the specified working environment. The stability data of the mechanical measurement component obtained in step S13 and the geometric structure data are input into the dynamic analysis software for dynamic characteristic analysis. Dynamic analysis mainly uses finite element simulation technology (FEA), such as dynamic response simulation through ABAQUS, ANSYS and other software. Based on the results of stability analysis, the software calculates the dynamic response of the mechanical measurement component under different excitation conditions, including vibration mode, natural frequency, modal analysis, etc.This process needs to take into account the material properties, structural characteristics and the impact of external loads on the dynamic behavior of the components, and obtain the dynamic characteristic data of the mechanical measurement components, such as resonant frequency, vibration amplitude, vibration mode, etc. For complex mechanical systems, detailed modeling of factors such as component connection methods, interface friction, and interaction is also required in order to more realistically simulate the dynamic behavior at work.

[0097] Preferably, step S13 comprises the following steps:

[0098] Step S131: collecting the material of the mechanical measurement component according to the mechanical measurement component design data to obtain the material data of the mechanical measurement component;

[0099] Step S132: Calculate the material strength of the mechanical measurement component according to the material data of the mechanical measurement component to obtain the material strength data of the mechanical measurement component;

[0100] Step S133: Calculate the arc of the measuring point of the mechanical measuring component according to the geometric structure data of the mechanical measuring component to obtain the arc data of the measuring point of the mechanical measuring component;

[0101] Step S134: performing bending stiffness analysis of the mechanical measurement component based on the arc data of the mechanical measurement component measurement point and the material strength data of the mechanical measurement component to obtain bending stiffness data of the mechanical measurement component;

[0102] Step S135: Predicting the stress and deformation of the mechanical measurement component bending stiffness data and the arc data of the mechanical measurement component measurement point to obtain stress and deformation data of the measurement component;

[0103] Step S137: performing stability analysis on the mechanical measurement component according to the bending stiffness data of the mechanical measurement component and the force deformation data of the measurement component to obtain stability data of the mechanical measurement component.

[0104] In an embodiment of the present invention, material-related data is extracted from the design file of the mechanical measurement component. These material data include but are not limited to the type, grade, density, elastic modulus, yield strength, tensile strength, etc. of the material. This information is usually contained in the CAD design file, engineering material table or technical specification of the component. If the design data does not clearly give the material information, it is necessary to refer to the design specification or perform physical detection, and measure the material composition through equipment such as a metal analyzer or a spectrometer to obtain accurate data of the material. For composite materials or special functional materials, more sophisticated analysis methods are required, such as scanning electron microscopy (SEM) or X-ray diffraction (XRD), etc. The core of this step is to accurately obtain the material data of the component, and use the material mechanics model to calculate the material strength based on the material data of the mechanical measurement component collected in step S131. Strength calculation requires clear basic mechanical properties of the material used in the component, such as yield strength, tensile strength, shear strength, fracture toughness, etc. These data are usually found in the standard material database or determined by experiment. Use relevant strength theories (such as yield criterion, strength limit criterion, etc.) to calculate the material of the component and evaluate its bearing capacity under different loading conditions. For example, the Von Mises criterion or the Tresca criterion is used to evaluate the yield condition of the material under complex loads. When calculating, factors such as the stress-strain relationship of the material, the temperature effect, and the loading rate need to be considered. Based on these data, the material strength data is obtained. The implementation of step S133 depends on the geometric structure data of the mechanical measurement component. The bending curvature of the key measurement points on the component is calculated by mathematical formulas or numerical methods. The position of the measurement points on the component needs to be determined. These points are the surface points, support points, or connection points of the component. According to the coordinates of these measurement points in the geometric model, the bending curvature is calculated using the bending mechanics formula or the finite element method. The bending curvature is a key parameter that describes the degree of bending of the component under the action of external force, usually expressed as a bending radius or a bending angle. In this process, the bending performance of the component under the working load is evaluated in combination with the material properties and geometric shape of the component, and the bending value of each measurement point is calculated. For components with complex shapes, finite element analysis (FEA) software, such as ANSYS, ABAQUS, etc., is required to perform simulation calculations to obtain more accurate bending curvature data. The bending curvature data of the measuring point obtained in step S133 is combined with the material strength data to perform bending stiffness analysis of the component. Bending stiffness is a physical quantity that describes the material's ability to resist deformation under bending force, usually expressed by the ratio of bending moment to deflection. Using the bending equation in material mechanics, the bending stiffness of the component is calculated based on the component's geometric structure (such as cross-sectional shape, size, etc.) and material properties (such as elastic modulus, yield strength, etc.). In actual operation, it is necessary to combine engineering software such as MATLAB, ABAQUS or specialized bending analysis tools for accurate simulation and calculation.These analyses will obtain the bending stiffness data of the components under different load conditions. The bending stiffness data obtained in step S134 and the bending data of the measuring point are used, combined with the stress conditions under the external force, to estimate the stress deformation of the components under the actual working environment. This step requires the use of statics and dynamics analysis methods to apply predetermined load conditions (such as external force, temperature change, vibration, etc.) to the components, and to infer the deformation of the components after the stress is applied through the mechanical model. In this process, finite element software is required for simulation calculations, and the specific steps include: inputting the geometric data, material strength, bending stiffness, applied load and boundary conditions of the components, and then solving the deformation amount, deformation shape and stress distribution of the components. Based on the obtained bending stiffness data and stress deformation data, the mechanical measurement components are subjected to stability analysis. This analysis process takes into account the overall deformation, yielding, fracture and other phenomena of the components under the working load. Through the finite element analysis method, all physical properties of the components (such as material, geometry, load, bending stiffness, etc.) are input into the software model to analyze the stress distribution, deformation mode and instability area of ​​the components after the stress is applied. For example, whether there are areas of the component that exceed the yield strength, whether there are failures caused by excessive bending, etc. Through this analysis, the stability data of the mechanical measurement component is obtained, including the load-bearing capacity, extreme working conditions and failure modes of the component under different working conditions. Based on the obtained bending stiffness data and stress deformation data, the stability analysis of the mechanical measurement component is carried out. This analysis process takes into account the overall deformation, yielding, fracture and other phenomena of the component under the working load. Through the finite element analysis method, all the physical properties of the component (such as material, geometry, load, bending stiffness, etc.) are input into the software model to analyze the stress distribution, deformation mode and unstable area of ​​the component after being stressed. For example, whether there are areas of the component that exceed the yield strength, whether there are failures caused by excessive bending, etc. Through this analysis, the stability data of the mechanical measurement component is obtained.

[0105] Preferably, step S14 comprises the following steps:

[0106] Step S141: collecting the motion trajectory of the mechanical measurement component according to the geometric structure data of the mechanical measurement component to obtain the motion trajectory data of the mechanical measurement component;

[0107] Step S142: measuring the clearance of the sliding axis of the mechanical measuring component according to the geometric structure data of the mechanical measuring component and the motion trajectory data of the mechanical measuring component to obtain the clearance data of the sliding axis of the mechanical measuring component;

[0108] Step S143: Calculating the friction coefficient of the mechanical measurement component based on the mechanical measurement component sliding axis point clearance data and the mechanical measurement component design data to obtain the mechanical measurement component friction coefficient data;

[0109] Step S144: estimating the sliding smoothness of the measuring component according to the friction coefficient data of the mechanical measuring component and the stability data of the mechanical measuring component to obtain the sliding smoothness data of the measuring component;

[0110] Step S145: Calculate the influence of the measuring component accuracy according to the measuring component sliding smoothness data, the mechanical measuring component stability data and the mechanical measuring component friction coefficient data to obtain the measuring component accuracy influence data;

[0111] Step S146: Performing a dynamic characteristic analysis of the mechanical measuring component based on the measuring component accuracy influence data and the measuring component sliding smoothness data to obtain the mechanical measuring component dynamic characteristic data.

[0112] In the embodiment of the present invention, based on the geometric structure data of the mechanical measurement component, the motion trajectory of the component is collected by mathematical modeling or numerical simulation technology, and all relevant geometric data, especially the relative position relationship and motion constraint of the moving component, are extracted from the design drawings of the mechanical measurement component. Using the principle of kinematics, a kinematic model is established through information such as the connection mode, joint type, and drive mode of the component, so as to simulate the motion process of the mechanical component under the working state. Specifically, kinematic formulas or simulation software (such as SolidWorks, ADAMS, etc.) are used to calculate and track the position and posture of the component under each time step. During the simulation process, considering factors such as friction and inertial force, the motion trajectory of the component at each critical moment is recorded, and the motion trajectory data of the component in the entire working cycle are obtained. These data contain information such as the position, speed and acceleration of the component in each state. The obtained mechanical measurement component motion trajectory data is used, combined with the geometric structure data of the component, to find the axis point position of the mechanical measurement component, and measure the sliding axis point gap. Through the geometric data of the component, the position of the sliding axis point is determined, and these axis points are usually the places where the components slide together, such as the contact points between the slider and the guide rail. Next, the relative position changes between these sliding axis points under different working conditions are calculated in combination with the motion trajectory data, thereby obtaining the axis point clearance. During the measurement process, a precision three-dimensional coordinate measuring machine (CMM) or laser scanner is used to measure the components to obtain the difference between the actual size of the components and the design size. By measuring multiple axis points, a comprehensive sliding axis point clearance data set is obtained. By combining the sliding axis point clearance data and design data of the components, the friction coefficient of the mechanical measurement component is calculated. The friction coefficient is a key parameter that determines the sliding performance of mechanical components. Its size directly affects the movement efficiency and heat generation of the components. The design data of the components (such as material type, surface roughness, etc.) is used to preliminarily estimate the friction coefficient. Combined with the measured axis point clearance data, how the size of the gap affects the friction characteristics of the contact surface is evaluated. The friction coefficient data under different working conditions is obtained through theoretical calculations or experimental methods (such as sliding friction experiments or using a friction tester). This process is optimized in combination with the mechanical model of sliding contact. For example, the Amontons law is used to calculate the relationship between static friction and dynamic friction, and the friction coefficient data is further obtained. The obtained friction coefficient data and the stability data of the mechanical measurement component are used to estimate the sliding smoothness. Sliding smoothness is an important parameter that describes whether the movement of a component is smooth and stable during operation. In this step, the resistance between the sliding surfaces is determined based on the friction coefficient data, and the movement behavior of the mechanical component under different friction conditions is evaluated in combination with the dynamic model. By calculating the relative motion and interaction force of each axis point, the sliding response under different load and speed conditions is simulated to evaluate the sliding smoothness of the component.Mathematical modeling and dynamic simulation technology are used to construct a sliding system model under the action of friction, inertia and external force, determine the conditions for vibration, jumping or irregular motion, obtain the sliding stability data of the component under a specific working environment, and combine the sliding stability data, stability data and friction coefficient data obtained in step S144 to calculate the influence of the accuracy of the measuring component. The accuracy of mechanical components is greatly affected by sliding stability and friction. The influence of vibration and friction fluctuations during sliding on the positioning accuracy of components is evaluated through sliding stability data. Then, combined with the stability data of the component, the matching degree of motion accuracy and component design under different working conditions is analyzed. The accuracy changes of components under working conditions are monitored by precision measuring tools (such as laser interferometers, optical sensors, etc.), and the reasons for the accuracy changes are analyzed by theoretical models. Through comprehensive analysis of various data, the accuracy influence data of the measuring component under different operating conditions are obtained, and the dynamic characteristics of the mechanical measuring component are analyzed by combining the accuracy influence data of the measuring component obtained in step S145 with the sliding stability data. By modeling the motion behavior of components under different working conditions, their dynamic response is analyzed, including the influence of motion speed, acceleration, inertia force, friction force, etc. on the overall performance of the components. In this process, it is necessary to establish a dynamic model of the mechanical components, including all relevant mechanical parameters and constraints. Then, the components are simulated using finite element analysis (FEA) or multi-body dynamics (MBD) simulation software (such as ANSYS, MSC Adams, etc.) to obtain dynamic characteristic data under different load conditions. By analyzing the dynamic response of the components, the motion deviation, overload phenomenon or efficiency loss that occurs during the working process is predicted, and comprehensive dynamic characteristic data is obtained.

[0113] Preferably, step S2 comprises the following steps:

[0114] Step S21: performing optical characteristic analysis of the mechanical measurement component according to the mechanical measurement component design data to obtain optical characteristic data of the mechanical measurement component;

[0115] Step S22: constructing an optical three-dimensional model of the mechanical measurement component based on the optical characteristic data of the mechanical measurement component, the geometric structure data of the mechanical measurement component, and the dynamic characteristic data of the mechanical measurement component to obtain an optical three-dimensional model of the mechanical measurement component;

[0116] Step S23: performing multi-level resolution segmentation according to the three-dimensional model of the mechanical measurement component to obtain multi-level resolution segmentation data of the three-dimensional model;

[0117] Step S24: performing multi-view acquisition of the mechanical measurement component according to the multi-level resolution segmentation data of the three-dimensional model to obtain multi-view data of the movement of the mechanical measurement component.

[0118] As an example of the present invention, refer to Figure 2 As shown, in this example, step S2 includes:

[0119] Step S21: performing optical characteristic analysis of the mechanical measurement component according to the mechanical measurement component design data to obtain optical characteristic data of the mechanical measurement component;

[0120] In an embodiment of the present invention, the design data of the mechanical measurement component is obtained, including the geometric shape, surface roughness, material and optical properties of the component. These data will serve as the basis for subsequent optical feature analysis. Next, the surface of the component is evaluated in detail using an optical analysis method to analyze its optical properties such as reflection, refraction, and transmittance, especially the effects of reflectivity and surface finish on the performance of the optical sensor. Optical simulation software (such as Zemax, LightTools, etc.) can be used for analysis, considering the changes in reflected light on the surface of the component under different light source angles and receiving angles. Optical feature analysis not only needs to consider the basic propagation characteristics of light, but also needs to analyze how the microstructure of the component surface (such as surface roughness and texture) affects the propagation of light, and obtain key data reflecting the optical performance of the component, including reflectivity, refractive index, surface texture parameters, etc.

[0121] Step S22: constructing an optical three-dimensional model of the mechanical measurement component based on the optical characteristic data of the mechanical measurement component, the geometric structure data of the mechanical measurement component, and the dynamic characteristic data of the mechanical measurement component to obtain an optical three-dimensional model of the mechanical measurement component;

[0122] In an embodiment of the present invention, the optical characteristic data, geometric structure data and dynamic characteristic data of the mechanical measurement component obtained in step S21 are collected. These data provide comprehensive information for establishing an accurate optical three-dimensional model. Based on these data, computer-aided design (CAD) software, such as SolidWorks or Autodesk Inventor, is used to accurately model the geometric structure of the component. On this basis, the optical characteristic data is integrated into the three-dimensional model to simulate the optical performance of the component under different lighting conditions. During the construction process, the behaviors such as refraction and reflection of light are considered, especially how the optical properties of the surface of the component interact with the geometric structure to affect the overall optical effect. In addition, considering the dynamic characteristics of the component, such as vibration, motion, etc., the optical effect will also be affected, so it is necessary to simulate these dynamic effects in the three-dimensional model. The established three-dimensional model is further optimized using optical simulation software (such as Zemax, TracePro, etc.) to ensure the accurate simulation of optical performance, and the optical three-dimensional model obtained reflects the comprehensive influence of the optical properties, geometric shape and motion behavior of the component.

[0123] Step S23: performing multi-level resolution segmentation according to the three-dimensional model of the mechanical measurement component to obtain multi-level resolution segmentation data of the three-dimensional model;

[0124] In an embodiment of the present invention, the optical three-dimensional model of the mechanical measurement component obtained in step S22 is used to perform multi-level resolution segmentation. Multi-level resolution segmentation refers to dividing the three-dimensional model into a plurality of sub-areas with different resolutions so as to select the appropriate resolution for rendering as needed under different viewing angles. In this process, the three-dimensional model is segmented using a three-dimensional grid processing technology (such as an octree, a quadtree, or a subdivision surface, etc.) so that the model has a higher resolution in the area close to the viewpoint, while a lower resolution is used in the area far from the viewpoint. In specific implementation, different resolution strategies are selected according to the viewing angle information and rendering requirements. The model is segmented using a three-dimensional modeling software (such as Maya, Blender, Unity3D, etc.) to generate three-dimensional model data containing multiple resolution levels. The data set will contain vertex data, texture mapping information, etc. in different areas, and can load and render the multi-level resolution segmentation data obtained in real time according to the change in viewing distance.

[0125] Step S24: performing multi-view acquisition of the mechanical measurement component according to the multi-level resolution segmentation data of the three-dimensional model to obtain multi-view data of the movement of the mechanical measurement component.

[0126] In an embodiment of the present invention, based on the multi-level resolution segmentation data of the three-dimensional model obtained in step S23, multi-view acquisition of mechanical measurement components is performed. Multi-view acquisition refers to the acquisition of images or videos of mechanical measurement components from multiple different observation angles or camera positions to simulate the different perspectives seen by the human eye, using high-precision multi-lens shooting equipment or multiple cameras set at different angles to shoot around mechanical components. Ensure that these perspectives cover the key parts of the mechanical components and can accurately reflect their changes in motion. Combined with a multi-view acquisition system (such as a stereo camera array or a panoramic camera array), image data from different angles is obtained through different perspectives. To ensure the accuracy of the perspective data, a special multi-view image processing software can be used for image fusion and correction to ensure that the data from each perspective can consistently reflect the motion state of the component. Through motion capture technology or multi-camera image correction, the motion process of the component is accurately recorded to generate multi-view data.

[0127] Preferably, step S21 includes the following steps:

[0128] Step S211: performing physical property detection of the mechanical measurement component on the mechanical measurement component design data to obtain physical property data of the mechanical measurement component;

[0129] Step S212: performing surface roughness detection of the mechanical measurement component according to the physical property data of the mechanical measurement component to obtain surface roughness data of the mechanical measurement component;

[0130] Step S213: performing texture feature analysis of the mechanical measurement component based on the surface roughness data of the mechanical measurement component to obtain texture feature data of the mechanical measurement component;

[0131] Step S214: calculating the component surface reflectivity according to the mechanical measurement component texture feature data and the mechanical measurement component surface roughness data to obtain the component surface reflectivity data;

[0132] Step S215: Analyze the visual effect of the component based on the component surface reflectivity data and the mechanical measurement component texture feature data to obtain the mechanical measurement component visual effect data;

[0133] Step S216: performing optical characteristic analysis of the mechanical measurement component according to the visual effect data of the mechanical measurement component and the component surface reflectivity data to obtain the optical characteristic data of the mechanical measurement component.

[0134] In an embodiment of the present invention, it is necessary to collect design data of the mechanical measurement component, including information such as material, geometry, and size. Physical property detection technology is used to comprehensively evaluate the material properties of the component, especially important physical properties such as density, elastic modulus, thermal conductivity, and electrical conductivity of the component. Standard physical testing methods, such as tensile tests, hardness tests, thermal expansion tests, etc., are used to determine the various physical parameters of the component. For example, an electronic universal testing machine is used to perform tensile or compression tests to test the stress-strain relationship of the sample to obtain data such as its elastic modulus; a thermal expansion meter is used to test the linear expansion coefficient of the component under different temperature conditions. These physical property data can provide accurate basic data for subsequent optical property analysis. Based on the obtained physical property data, the surface roughness of the mechanical measurement component is detected. Surface roughness is an important factor affecting the optical properties of components, especially in optical behaviors such as light reflection, refraction, and transmission. It plays a key role. In order to detect the surface roughness, a surface profiler (such as a white light interferometer or a laser scanner) is used to obtain the detailed features of the surface through high-precision three-dimensional scanning technology. The surface profiler provides micrometer-level or even nanometer-level measurement accuracy, generates a surface profile map, and then calculates the average surface roughness Ra, maximum roughness Rz and other parameters. During the specific operation, the profiler is contacted or non-contacted with the surface of the mechanical measurement component to generate point cloud data, extract the surface roughness data obtained by the roughness feature, and further perform the texture feature analysis of the mechanical measurement component based on the surface roughness data obtained in step S212. The surface texture of the mechanical component directly affects the scattering and reflection behavior of light, so it is necessary to analyze its texture features, calculate the features of the surface details such as wavelength, frequency, directivity, etc. through the surface roughness data, and use image processing and analysis techniques (such as Fourier transform, grayscale co-occurrence matrix, etc.) to quantitatively describe the surface texture. Use professional surface texture analysis tools (such as MetLog, ImageJ, etc.) to image the surface, and obtain feature data by extracting texture parameters such as texture direction, texture period, surface ripples, etc. The surface reflectivity of the mechanical measurement component is calculated based on the texture feature data and the surface roughness data. Surface reflectivity refers to the reflection efficiency of the object surface to the incident light. It is affected by factors such as surface roughness, texture, and material. The reflectivity under different angles and different incident light conditions is calculated using an optical reflection model (such as the Fresnel formula or ray tracing method). According to the surface texture and roughness characteristics of the component, a statistical scattering model (such as the Lambertian reflection model) is used to model the surface to simulate the interaction between light and the component surface. Optical simulation software (such as Zemax, LightTools, etc.) is used for calculation, considering the influence of different textures and roughness on the reflectivity, and the reflectivity data of the component is obtained.Using the surface reflection ability data obtained in step S214 and the texture feature data obtained in step S213, further perform visual effect analysis of the mechanical measurement component. The visual effect analysis aims to simulate the visual performance of the component under different lighting conditions, with a focus on the reflection, refraction, scattering of the component surface and the interactive effects with the surrounding environment. By combining the reflection model with the texture features and adopting lighting models in computer graphics (such as the Phong lighting model or the Blinn-Phong model), simulate the interaction between the light source and the component surface, and calculate the intensity, color distribution and surface detail effects of the reflected light. In addition, use a rendering engine (such as V-Ray, Arnold, etc.) to model the lighting environment, generate realistic visual effect images, and obtain visual effect data, including information such as reflected light distribution, luminance, and color saturation. Based on the obtained visual effect data and the surface reflection ability data, further perform optical feature analysis of the mechanical measurement component. The main purpose of this step is to analyze the overall optical performance of the mechanical measurement component under various lighting environments, comprehensively considering optical behaviors such as reflection, refraction, and transmission. By establishing an optical characteristic model, comprehensively analyze the parameters such as reflection, scattering, and transmission on the component surface with the visual effect data to obtain the complete optical characteristics of the component. Use optical simulation software (such as LightTools, Zemax, etc.) to conduct a comprehensive optical performance evaluation of the component, and optimize the optical characteristic parameters according to the changes in the reflection ability and visual effects to obtain the optical characteristic data.

[0135] Preferably, step S3 includes the following steps:

[0136] Step S31: Construct a disparity map of the mechanical measurement component based on the multi-view data of the mechanical measurement component's movement to obtain the mechanical measurement component disparity map data;

[0137] Step S32: Based on the mechanical measurement component disparity map data, perform detailed rendering adjustment to obtain the mechanical measurement component detailed rendering data;

[0138] Step S33: Based on the mechanical measurement component detailed rendering data and the mechanical measurement component disparity map data, construct a digital virtual naked-eye 3D display image to obtain the digital virtual human naked-eye 3D display image data.

[0139] In an embodiment of the present invention, it is necessary to collect multi-view data of the motion of the mechanical measurement component, which obtains the image information of the component at different viewing angles through multiple cameras or multi-angle sensors. According to the image data obtained by shooting at different angles, the disparity between each pair of images is extracted using image processing technology. The construction of the disparity map depends on the stereo matching algorithm, and the images of each viewing angle are aligned and preprocessed (such as graying, denoising, edge enhancement, etc.), and then the traditional stereo vision algorithm, such as block matching algorithm (Block Matching) or dynamic programming algorithm, is applied to calculate the disparity value of each pixel in the image. The disparity value represents the difference between the two viewing angles of objects at different depths in the scene, and then a disparity map reflecting the three-dimensional form of the object is constructed. The obtained disparity map data provides three-dimensional depth information about the shape, position and spatial relationship of the component. Based on the disparity map data obtained in step S31, detail rendering adjustment is performed to enhance the visual effect and authenticity of the image. Detail rendering is mainly performed in the following aspects: for the noise and detail loss in the disparity map, smoothing and enhancement techniques, such as Gaussian filtering and edge sharpening techniques, are applied to remove image noise and improve the fineness of the object surface. Secondly, according to the depth information in the disparity map data, the illumination model is adjusted to simulate the illumination changes under different light source conditions, and enhance the stereoscopic and realistic sense of the object surface. At this time, optical effects such as light reflection, scattering, and refraction are introduced, such as diffuse reflection and specular reflection, so as to better present the details of the object surface. At the same time, texture mapping technology can be used to add more realistic texture patterns to the surface of the object, further improve its detail performance, perform color correction and light and shadow effect processing, and ensure the consistency and fidelity of the performance of the rendered image on different display devices. Through this series of adjustments, the obtained detail rendering data contains optimized visual effects and surface detail information, and the detail rendering data obtained in step S32 is used to jointly construct a digital virtual naked-eye 3D display image with the disparity map data obtained in step S31, and the detail rendering data is combined with the disparity map data to ensure that the three-dimensional depth and visual effect of the virtual object are highly consistent. At this time, naked-eye 3D display technology, such as light field display or multi-view display technology, is required to present a stereoscopic effect. Light field display technology splits the rendered image into image data from multiple perspectives and arranges these images at different angles on the display panel, so that the audience can feel the image effects from different perspectives without wearing glasses. To achieve this goal, special display screens, such as multi-perspective display screens or naked-eye 3D display screens, are used in combination with microlens array technology or parallax barrier technology to present the three-dimensional effect of virtual objects. At the same time, the parallax map data provides depth information for each perspective, allowing different viewers to view different three-dimensional representations of objects from different perspectives. After the construction is completed, the generated digital virtual naked-eye 3D display image data contains multi-angle, multi-level parallax information and detailed rendering effects of the object.

[0140] Preferably, step S32 includes the following steps:

[0141] Step S311: collecting a stereo image pair according to the multi-view data of the movement of the mechanical measurement component to obtain the stereo image pair data of the mechanical measurement component;

[0142] Step S312: performing image grayscale processing on the stereo image pair data of the mechanical measurement component to obtain stereo image pair image grayscale data;

[0143] Step S313: calculating the disparity value of the image pair based on the grayscale data of the stereo image pair to obtain the disparity value data of the stereo image pair;

[0144] Step S314: performing grayscale image mapping on the image disparity value data according to the stereo image to obtain disparity value grayscale image mapping data;

[0145] Step S315: constructing a mechanical measurement component disparity map based on the disparity value grayscale image mapping data and the stereo image disparity value data to obtain mechanical measurement component disparity map data.

[0146] In an embodiment of the present invention, a plurality of cameras or sensors are used to shoot the mechanical measurement component from different viewing angles. Each camera should capture images at different positions and angles to ensure that multi-angle information of the surface of the object can be captured. Each pair of images should be a stereoscopic image pair, one of which is taken from the left viewing angle and the other is taken from the right viewing angle. The image data at these viewing angles are collected by special hardware devices (such as stereo cameras, 3D scanners, etc.), and usually the shooting conditions of each pair of images need to be consistent, such as light intensity, camera focal length, etc., so as to ensure that the contrast and clarity of the image can be kept consistent to the greatest extent. During the acquisition process, it is necessary to monitor the image quality to ensure that the acquired image data can clearly show the edges, textures and surface details of the components. The stereoscopic image pair data of the mechanical measurement component obtained in step S311 is grayed. Image graying is the process of converting a color image into a black and white (grayscale) image, the purpose of which is to simplify the image data and remove the influence of color on the image processing process. The specific operation is to convert the RGB color value of each pixel into a single grayscale value through an image processing algorithm (such as a weighted average method). The grayscale value is calculated by weighted averaging the intensity of the red, green and blue channels of each pixel in the image to obtain a grayscale value representing the brightness intensity. The grayscaled image is more convenient for subsequent stereo matching and disparity calculation. After removing the color information, the texture, edge and other details of the object in the image are more clearly displayed, and the complexity of the calculation can be effectively reduced. In this process, image processing tools and algorithms, such as the grayscale function in the OpenCV library, are used to quickly convert the original color image. Based on the grayscaled image data, the disparity value of the pixel points in each pair of stereo images is calculated by the stereo matching algorithm. The disparity value represents the horizontal position offset of the pixel points at the same position on the surface of the object in the images taken from two different perspectives (left and right). In the process of calculating the disparity value, the feature areas in the image, such as edges, corners, etc., are selected as the reference points for matching. Then, the block matching algorithm, dynamic programming algorithm or graph cut algorithm are used to match the pixels. The disparity value is determined by comparing the grayscale difference of the corresponding pixel areas in the left and right images. The larger the disparity value, the closer the pixel is to the observer, and vice versa, the farther the object is. The disparity values ​​of all pixels will be calculated to form a set of disparity value data. This process relies on deep learning and optimization algorithms in the fields of computer vision and image processing to improve matching accuracy and reduce mismatches and calculation deviations. The calculated disparity value data is mapped to a grayscale image to form a visual expression of the disparity value. Specifically, each disparity value is mapped one-to-one to a grayscale level. Generally, the larger the disparity value, the brighter the corresponding grayscale value. During the mapping process, a suitable grayscale level range is defined, such as from 0 to 255, and the calculated disparity values ​​are normalized according to this range.A grayscale value is assigned to each pixel according to the normalized disparity value, thereby forming a new grayscale image. In this image, the brightness reflects the size of the disparity, the brighter area represents the part of the object closer to the observer, and the darker area represents the part of the object farther from the observer. Based on the disparity value grayscale image mapping data obtained in step S314 and the calculated stereo image pair disparity value data, a disparity map of the mechanical measurement component is constructed. The construction process of the disparity map involves combining the mapped grayscale image with the corresponding depth information. Through image processing and computer vision algorithms, the disparity map is associated with the actual mechanical component geometry to generate accurate three-dimensional depth data. The specific operation includes converting each grayscale value in the disparity map into an actual depth value to construct an image reflecting the relative position and depth of the object in three-dimensional space. These depth information helps to present the undulations on the surface of the object and reflect the three-dimensional structure of the object. Generated disparity map data of the mechanical measurement component.

[0147] Preferably, step S4 comprises the following steps:

[0148] Step S41: estimating the distortion status of naked-eye 3D display based on the naked-eye 3D display image data of the digital virtual human to obtain the distortion status data of the naked-eye 3D display;

[0149] Step S42: performing mechanical component detail loss detection based on naked-eye 3D display distortion status data to obtain naked-eye 3D detail loss data of mechanical measurement components;

[0150] Step S43: performing naked-eye 3D abnormality analysis on the mechanical measuring component according to the naked-eye 3D detail loss data and the naked-eye 3D display distortion status data of the mechanical measuring component to obtain naked-eye 3D abnormality data of the mechanical measuring component;

[0151] Step S44: performing naked-eye 3D optical characteristic correction on the digital virtual naked-eye 3D display image data according to the naked-eye 3D abnormal data of the mechanical measurement component to obtain naked-eye 3D optical characteristic correction data.

[0152] As an example of the present invention, refer to Figure 3 As shown, in this example, step S4 includes:

[0153] Step S41: estimating the distortion status of naked-eye 3D display based on the naked-eye 3D display image data of the digital virtual human to obtain the distortion status data of the naked-eye 3D display;

[0154] In an embodiment of the present invention, the distortion phenomenon of naked-eye 3D display is estimated by analyzing the naked-eye 3D display image data of the digital virtual human. The distortion condition is caused by multiple factors, such as the resolution limitation of the display device, the distortion of the optical system, the viewing angle error, the local depth distortion of the displayed content, etc. The specific operation includes a comprehensive analysis of the geometric morphology, depth information and brightness contrast of the displayed image, and the use of a special distortion evaluation algorithm (such as a distortion simulation model or a physics-based optical simulation method) to predict the image changes under different viewing angles and display angles. The distortion estimation process also includes fine detection of different areas of the displayed image to determine whether there are phenomena such as image blur, color distortion, depth distortion or motion artifacts. In addition, combined with the actual performance of the display device, such as viewing angle limitation, resolution, etc., mathematical modeling is used to quantitatively predict potential distortion problems. Through these analyses, the naked-eye 3D display distortion condition data is obtained.

[0155] Step S42: performing mechanical component detail loss detection based on naked-eye 3D display distortion status data to obtain naked-eye 3D detail loss data of mechanical measurement components;

[0156] In an embodiment of the present invention, the naked-eye 3D display distortion status data obtained in step S41 is used to detect the loss of details of mechanical parts. The core of this process is to quantitatively analyze the details of the displayed image to identify which parts of the geometric details, textures or depth information are lost or cannot be accurately presented during the naked-eye 3D display process, and to detect whether there are details lost due to the resolution limitation or distortion of the display device by comparing the original three-dimensional model data with the details in the displayed image. This includes phenomena such as edge distortion in local areas, blurring of details, and disappearance of local reflected light. Image quality assessment algorithms (such as edge detection algorithms, texture analysis algorithms, etc.) are used to identify changes in details in the displayed image. At the same time, based on the texture and surface information of the mechanical measurement parts, optical simulation and analysis tools are used to evaluate whether the distorted area will affect the display of key details, such as surface roughness, texture, and fine structure, to obtain naked-eye 3D detail loss data of the mechanical measurement parts.

[0157] Step S43: performing naked-eye 3D abnormality analysis on the mechanical measuring component according to the naked-eye 3D detail loss data and the naked-eye 3D display distortion status data of the mechanical measuring component to obtain naked-eye 3D abnormality data of the mechanical measuring component;

[0158] In an embodiment of the present invention, the naked-eye 3D detail loss data obtained in step S42 and the naked-eye 3D display distortion status data obtained in step S41 are combined to perform naked-eye 3D abnormal analysis of the mechanical measurement component. The goal of the abnormal analysis is to identify abnormal visual effects caused by detail loss or display distortion during the naked-eye 3D display process, such as component surface distortion, depth dislocation, texture error, etc., by combining the detail loss area with the display distortion status to analyze the comprehensive effect produced during the display process. For example, detail loss causes the geometric shape of the object to be blurred, while display distortion causes the depth error of the object. Combined with the data collected from multiple perspectives, image reconstruction and reverse analysis techniques are used to track the specific location and severity of these distortions or detail losses. In addition, by calculating the error propagation model, the degree of influence of detail loss and distortion on the overall naked-eye 3D effect is evaluated to form naked-eye 3D abnormal data of the mechanical measurement component.

[0159] Step S44: performing naked-eye 3D optical characteristic correction on the digital virtual naked-eye 3D display image data according to the naked-eye 3D abnormal data of the mechanical measurement component to obtain naked-eye 3D optical characteristic correction data.

[0160] In an embodiment of the present invention, the naked eye 3D optical property correction is performed according to the naked eye 3D abnormal data of the mechanical measurement component obtained in step S43. The core of this step is to adjust the optical properties of the digital virtual naked eye 3D display image according to the above-mentioned abnormal analysis results, so that the distortion and detail loss are effectively corrected, thereby optimizing the display effect, and identifying the optical problems existing in the display process according to the abnormal data, such as color shift, depth error or texture distortion. Next, the naked eye 3D display image is corrected using an optical simulation tool. This process includes adjusting the illumination model of the image, reflected light simulation, optical lens distortion compensation, etc., in order to ensure that the geometric shape, texture and depth information of the image can accurately reflect the original design. Optical property correction also needs to take into account the characteristics of the display device, such as viewing distance, resolution, and angle restrictions, and is adjusted through physical model simulation and optimization algorithms. The corrected data will present a more realistic and accurate naked eye 3D effect, and naked eye 3D optical property correction data will be obtained.

[0161] The present invention also provides a digital virtual human naked eye 3D display system, which is used to execute the digital virtual human naked eye 3D display method as described above, and the digital virtual human naked eye 3D display system comprises:

[0162] A dynamic characteristic analysis module is used to obtain the design data of the mechanical measurement component; collect the geometric structure of the mechanical measurement component according to the design data of the mechanical measurement component to obtain the geometric structure data of the mechanical measurement component; and analyze the dynamic characteristics of the mechanical measurement component based on the geometric structure data of the mechanical measurement component to obtain the dynamic characteristics data of the mechanical measurement component;

[0163] A component multi-view acquisition module is used to construct an optical three-dimensional model of a mechanical measurement component based on the mechanical measurement component design data, the mechanical measurement component geometric structure data, and the mechanical measurement component dynamic characteristic data to obtain an optical three-dimensional model of the mechanical measurement component; perform multi-view acquisition of the mechanical measurement component based on the optical three-dimensional model of the mechanical measurement component to obtain multi-view motion data of the mechanical measurement component;

[0164] A naked-eye 3D display image construction module is used to construct a parallax map of a mechanical measurement component according to the multi-view data of the movement of the mechanical measurement component to obtain the parallax map data of the mechanical measurement component; and to construct a digital virtual naked-eye 3D display image based on the parallax map data of the mechanical measurement component to obtain the naked-eye 3D display image data of a digital virtual human;

[0165] The naked-eye 3D optical property correction module is used to perform naked-eye 3D anomaly analysis of mechanical measurement components based on naked-eye 3D display image data of digital virtual humans to obtain naked-eye 3D anomaly data of mechanical measurement components; and perform naked-eye 3D optical property correction on digital virtual naked-eye 3D display image data according to naked-eye 3D anomaly data of mechanical measurement components to obtain naked-eye 3D optical property correction data.

[0166] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A method for naked-eye 3D display of digital virtual humans, characterized in that: The following steps are involved: Step S1: Acquire design data of a mechanical measurement component; collect the geometric structure of the mechanical measurement component according to the design data of the mechanical measurement component to obtain the geometric structure data of the mechanical measurement component; Performing dynamic characteristic analysis of the mechanical measurement component based on the geometric structure data of the mechanical measurement component to obtain dynamic characteristic data of the mechanical measurement component; Step S2: constructing an optical three-dimensional model of the mechanical measurement component based on the mechanical measurement component design data, the mechanical measurement component geometric structure data, and the mechanical measurement component dynamic characteristic data to obtain the optical three-dimensional model of the mechanical measurement component; performing multi-view acquisition of the mechanical measurement component according to the optical three-dimensional model of the mechanical measurement component to obtain multi-view motion data of the mechanical measurement component; Step S3: constructing a parallax map of the mechanical measurement component according to the multi-view data of the mechanical measurement component movement to obtain the parallax map data of the mechanical measurement component; constructing a digital virtual naked-eye 3D display image based on the parallax map data of the mechanical measurement component to obtain the naked-eye 3D display image data of the digital virtual human; Step S4: performing naked-eye 3D abnormality analysis of mechanical measurement components based on the naked-eye 3D display image data of the digital virtual human to obtain naked-eye 3D abnormality data of the mechanical measurement components; performing naked-eye 3D optical property correction on the digital virtual naked-eye 3D display image data according to the naked-eye 3D abnormality data of the mechanical measurement components to obtain naked-eye 3D optical property correction data.

2. The naked-eye 3D display method for digital virtual humans according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: Acquire mechanical measurement component design data; Step S12: collecting the geometric structure of the mechanical measurement component according to the design data of the mechanical measurement component to obtain the geometric structure data of the mechanical measurement component; Step S13: performing stability analysis on the mechanical measurement component based on the geometric structure data of the mechanical measurement component and the design data of the mechanical measurement component to obtain stability data of the mechanical measurement component; Step S14: performing a dynamic characteristic analysis of the mechanical measurement component based on the stability data of the mechanical measurement component and the geometric structure data of the mechanical measurement component to obtain the dynamic characteristic data of the mechanical measurement component.

3. The naked-eye 3D display method for digital virtual humans according to claim 2, characterized in that: Step S13 includes the following steps: Step S131: collecting the material of the mechanical measurement component according to the mechanical measurement component design data to obtain the material data of the mechanical measurement component; Step S132: Calculate the material strength of the mechanical measurement component according to the material data of the mechanical measurement component to obtain the material strength data of the mechanical measurement component; Step S133: Calculate the arc of the measuring point of the mechanical measuring component according to the geometric structure data of the mechanical measuring component to obtain the arc data of the measuring point of the mechanical measuring component; Step S134: performing bending stiffness analysis of the mechanical measurement component based on the arc data of the mechanical measurement component measurement point and the material strength data of the mechanical measurement component to obtain bending stiffness data of the mechanical measurement component; Step S135: Predicting the stress and deformation of the mechanical measurement component bending stiffness data and the arc data of the mechanical measurement component measurement point to obtain stress and deformation data of the measurement component; Step S137: performing stability analysis on the mechanical measurement component according to the bending stiffness data of the mechanical measurement component and the force deformation data of the measurement component to obtain stability data of the mechanical measurement component.

4. The naked-eye 3D display method for digital virtual humans according to claim 2, characterized in that: Step S14 includes the following steps: Step S141: collecting the motion trajectory of the mechanical measurement component according to the geometric structure data of the mechanical measurement component to obtain the motion trajectory data of the mechanical measurement component; Step S142: measuring the clearance of the sliding axis of the mechanical measuring component according to the geometric structure data of the mechanical measuring component and the motion trajectory data of the mechanical measuring component to obtain the clearance data of the sliding axis of the mechanical measuring component; Step S143: Calculating the friction coefficient of the mechanical measurement component based on the mechanical measurement component sliding axis point clearance data and the mechanical measurement component design data to obtain the mechanical measurement component friction coefficient data; Step S144: estimating the sliding smoothness of the measuring component according to the friction coefficient data of the mechanical measuring component and the stability data of the mechanical measuring component to obtain the sliding smoothness data of the measuring component; Step S145: Calculate the influence of the measuring component accuracy according to the measuring component sliding smoothness data, the mechanical measuring component stability data and the mechanical measuring component friction coefficient data to obtain the measuring component accuracy influence data; Step S146: Performing a dynamic characteristic analysis of the mechanical measuring component based on the measuring component accuracy influence data and the measuring component sliding smoothness data to obtain the mechanical measuring component dynamic characteristic data.

5. The naked-eye 3D display method for digital virtual humans according to claim 3, characterized in that: Step S2 includes the following steps: Step S21: performing optical characteristic analysis of the mechanical measurement component according to the mechanical measurement component design data to obtain optical characteristic data of the mechanical measurement component; Step S22: constructing an optical three-dimensional model of the mechanical measurement component based on the optical characteristic data of the mechanical measurement component, the geometric structure data of the mechanical measurement component, and the dynamic characteristic data of the mechanical measurement component to obtain an optical three-dimensional model of the mechanical measurement component; Step S23: performing multi-level resolution segmentation according to the three-dimensional model of the mechanical measurement component to obtain multi-level resolution segmentation data of the three-dimensional model; Step S24: performing multi-view acquisition of the mechanical measurement component according to the multi-level resolution segmentation data of the three-dimensional model to obtain multi-view data of the movement of the mechanical measurement component.

6. The naked-eye 3D display method for digital virtual humans according to claim 5, characterized in that: Step S21 includes the following steps: Step S211: performing physical property detection of the mechanical measurement component on the mechanical measurement component design data to obtain physical property data of the mechanical measurement component; Step S212: performing surface roughness detection of the mechanical measurement component according to the physical property data of the mechanical measurement component to obtain surface roughness data of the mechanical measurement component; Step S213: performing texture feature analysis of the mechanical measurement component based on the surface roughness data of the mechanical measurement component to obtain texture feature data of the mechanical measurement component; Step S214: calculating the component surface reflectivity according to the mechanical measurement component texture feature data and the mechanical measurement component surface roughness data to obtain the component surface reflectivity data; Step S215: Analyze the visual effect of the component based on the component surface reflectivity data and the mechanical measurement component texture feature data to obtain the mechanical measurement component visual effect data; Step S216: performing optical characteristic analysis of the mechanical measurement component according to the visual effect data of the mechanical measurement component and the component surface reflectivity data to obtain the optical characteristic data of the mechanical measurement component.

7. The naked-eye 3D display method for digital virtual humans according to claim 1, characterized in that: Step S3 includes the following steps: Step S31: constructing a disparity map of the mechanical measurement component according to the multi-view data of the movement of the mechanical measurement component to obtain disparity map data of the mechanical measurement component; Step S32: performing detail rendering adjustment based on the mechanical measurement component disparity map data to obtain mechanical measurement component detail rendering data; Step S33: constructing a digital virtual naked-eye 3D display image based on the mechanical measurement component detail rendering data and the mechanical measurement component parallax map data to obtain digital virtual human naked-eye 3D display image data.

8. The naked-eye 3D display method for digital virtual humans according to claim 7, characterized in that: Step S31 includes the following steps: Step S311: collecting a stereo image pair according to the multi-view data of the movement of the mechanical measurement component to obtain the stereo image pair data of the mechanical measurement component; Step S312: performing image grayscale processing on the stereo image pair data of the mechanical measurement component to obtain stereo image pair image grayscale data; Step S313: calculating the disparity value of the image pair based on the grayscale data of the stereo image pair to obtain the disparity value data of the stereo image pair; Step S314: performing grayscale image mapping on the image disparity value data according to the stereo image to obtain disparity value grayscale image mapping data; Step S315: constructing a mechanical measurement component disparity map based on the disparity value grayscale image mapping data and the stereo image disparity value data to obtain mechanical measurement component disparity map data.

9. The naked-eye 3D display method for digital virtual humans according to claim 1, characterized in that: Step S4 includes the following steps: Step S41: estimating the distortion status of naked-eye 3D display based on the naked-eye 3D display image data of the digital virtual human to obtain the distortion status data of the naked-eye 3D display; Step S42: performing mechanical component detail loss detection based on naked-eye 3D display distortion status data to obtain naked-eye 3D detail loss data of mechanical measurement components; Step S43: performing naked-eye 3D abnormality analysis on the mechanical measuring component according to the naked-eye 3D detail loss data and the naked-eye 3D display distortion status data of the mechanical measuring component to obtain naked-eye 3D abnormality data of the mechanical measuring component; Step S44: performing naked-eye 3D optical characteristic correction on the digital virtual naked-eye 3D display image data according to the naked-eye 3D abnormal data of the mechanical measurement component to obtain naked-eye 3D optical characteristic correction data.

10. A naked-eye 3D display system for digital virtual humans, characterized in that: Used to execute the naked-eye 3D display method of digital virtual human as claimed in claim 1, the naked-eye 3D display system of digital virtual human comprises: A dynamic characteristic analysis module is used to obtain the design data of the mechanical measurement component; collect the geometric structure of the mechanical measurement component according to the design data of the mechanical measurement component to obtain the geometric structure data of the mechanical measurement component; and analyze the dynamic characteristics of the mechanical measurement component based on the geometric structure data of the mechanical measurement component to obtain the dynamic characteristics data of the mechanical measurement component; A component multi-view acquisition module is used to construct an optical three-dimensional model of a mechanical measurement component based on the mechanical measurement component design data, the mechanical measurement component geometric structure data, and the mechanical measurement component dynamic characteristic data to obtain an optical three-dimensional model of the mechanical measurement component; perform multi-view acquisition of the mechanical measurement component based on the optical three-dimensional model of the mechanical measurement component to obtain multi-view motion data of the mechanical measurement component; A naked-eye 3D display image construction module is used to construct a parallax map of a mechanical measurement component according to the multi-view data of the movement of the mechanical measurement component to obtain the parallax map data of the mechanical measurement component; and to construct a digital virtual naked-eye 3D display image based on the parallax map data of the mechanical measurement component to obtain the naked-eye 3D display image data of a digital virtual human; The naked-eye 3D optical property correction module is used to perform naked-eye 3D anomaly analysis of mechanical measurement components based on naked-eye 3D display image data of digital virtual humans to obtain naked-eye 3D anomaly data of mechanical measurement components; and perform naked-eye 3D optical property correction on digital virtual naked-eye 3D display image data according to naked-eye 3D anomaly data of mechanical measurement components to obtain naked-eye 3D optical property correction data.

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