Optimization of Mesh Model with 3D Edge Feature Constraints

被引:0
作者
Zhang H. [1 ]
Wang J. [1 ]
Xie X. [2 ]
机构
[1] School of Geomatics, Liaoning Technical University, Liaoning, Fuxin
[2] Key Laboratory for Environment Computation & Sustainability of Liaoning Province, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang
基金
中国国家自然科学基金;
关键词
3D edge points; edge constraints; energy function; gradient descent; mesh refinement; photometric consistency; regularization; variational method;
D O I
10.12082/dqxxkx.2024.230633
中图分类号
学科分类号
摘要
The dense point cloud of the urban scene reconstructed by Multi- View Stereo reconstruction technology (MVS) often contains noise, resulting in surface distortion of the generated model and loss of some edge features, which cannot well reflect the real information of the reconstructed target. To solve these problems, a variational method combining 3D edge constraints is proposed to optimize the mesh model. Based on the initial grid data obtained by MVS algorithm, the energy function is constructed by the variational principle, and the grid model optimization problem is transformed into an energy function minimization problem. Firstly, the initial grid model is reconstructed from the dense point cloud. Then, the energy function is constructed by using the luminosity consistency measure, using the vertex curvature as the smooth term, and using the three-dimensional edge point constraint as the additional constraint term. Finally, the gradient descent method is used to solve the minimum energy function iteratively, and the grid deformation is driven by discretizing the gradient change to the vertex of the triangle to optimize the model. In order to construct 3D edge constraints, 3D edges must be extracted first. In this paper, 2D edges are extracted from multi-view images first, and the 2D edges are represented as multi-segment lines according to the polar constraints. Then, the 2D multi-segment line nodes are restored as 3D edge points according to the polar constraints, and the 3D edge points of the recovery points are a series of 3D multi-segment lines representing the edge outline. Finally, the edge region of the mesh model is located by taking the vertex of the mesh model closest to the 3D edge point as the neighborhood point. In this way, 3D edge features are constructed. In order to verify the effectiveness of the proposed algorithm, two real outdoor scenes from the Strecha dataset and one real indoor scene from the ETH3D dataset are selected to evaluate the reconstruction results of the proposed algorithm. In addition, the efficiency of this algorithm is analyzed by comparisons with other algorithms. Experimental results show that the proposed algorithm can effectively improve the accuracy and integrity of the grid model and retain the edge features of the target better on the grid model. © 2024 Science Press. All rights reserved.
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页码:1138 / 1150
页数:12
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