Digital twinning method and system based on 3D model matching

A model matching and model technology, applied in the field of digital twins, can solve the problems of rough model generation, only focusing on the similarity of shape, and not considering the similarity of texture between the original object and the virtual model.

Active Publication Date: 2021-12-21
ZHEJIANG LAB
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Problems solved by technology

[0004] Patent CN 201310343131.5 discloses a realization method of automatic generation and online interaction of a three-dimensional digital model of a plane space structure. It is relatively rare to use the method of server and client, but the model generation is relatively rough, and only a simple background model such as a wall is generated. Body, windows, a

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  • Digital twinning method and system based on 3D model matching
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  • Digital twinning method and system based on 3D model matching

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Embodiment

[0102] The data type of this embodiment is aimed at 3D model picture data under different viewing angles, and the model of the database uses the open source 3D model dataset ShapeNet of Stanford University as the basic data.

[0103] Blender is used as the rendering software. Take the chair set in ShapeNet as an example. The code name of the chair set in ShapeNet is 03001627, and Blender loads each model in the chair set.

[0104] Then set the camera position, which is represented by three parameters, namely distance, altitude and azimuth. The distance is the distance from the center of the model to the camera, the altitude is the height of the camera (the position of the bottom surface of the model is a horizontal line), and the azimuth is the angle between the projection vector of the xz plane of the camera position in the three-dimensional coordinates and the positive direction vector of the x-axis, such as image 3 shown. The camera is facing the center of the model, and...

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Abstract

The invention discloses a digital twinning method and system based on 3D model matching. The method comprises four steps of model and texture training, model matching, texture fusion and scene placement. The model and texture training is an offline preprocessing step, and the model matching, the texture fusion and the scene placement are real-time processing steps. In the model training, a multi-viewpoint silhouette image is used to learn a three-dimensional structure, and polygon mesh three-dimensional reconstruction is realized. In the texture training, a texture flow is obtained through fixed UV mapping, and reasoning from 2D images to 3D textures is achieved. In the model matching, a reconstructed model and a model of a database are used for performing IOU iterative calculation, and the model with an IOU value closest to 1 is obtained as a matched specified model. In the texture fusion, the matched specified model is fused with the 3D texture flow subjected to texture reasoning to form a standard 3D model. In the scene placement, the 3D model is accurately placed in a 3D scene. According to the digital twinning method, the 3D model scene is automatically generated, and the digital twinning efficiency is improved.

Description

technical field [0001] The invention relates to the field of digital twins, in particular to a digital twin method and system based on 3D model matching. Background technique [0002] At present, most methods for automatic generation of 3D models only match simple data such as coordinates or model types with existing models, and do not use the latest deep neural network machine learning methods. For example, patent CN202010701243.3 discloses an automatic generation of tunnel 3D models The method includes: S1, establishing a graphic database, storing objects including two-dimensional design drawings and entity objects of three-dimensional models; S2, creating an external database for storing multiple design parameters input by users; S3, based on user input parameters to generate 2D design drawings and 3D models of tunnels. Patent CN202011386970.1 discloses a method for automatically generating a 3D model of a road intersection, including: obtaining the basic parameters of t...

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Application Information

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IPC IPC(8): G06T17/00G06T17/20G06T15/04G06K9/62
CPCG06T17/00G06T15/04G06T17/205G06F18/22
Inventor 金鑫宋伟朱世强顾建军姜淑瑾
Owner ZHEJIANG LAB
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