多角度单眼服装图像三维重建算法的研究与实现

Xinrong Hu, Xiao Zeng, Junping Liu, Tao Peng, R. He, Changnian Chen
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引用次数: 1

摘要

为了降低服装造型的构建难度,提高服装造型的构建效率。提出了一种基于单视角和多视角的服装三维重建方法。首先获得服装图像序列,然后对服装图像序列进行实例化和分割,得到包含服装部分的轮廓信息。采用SIFT算法提取每幅图像的特征点和匹配,并通过添加双约束消除匹配误差。然后分别对稀疏点云和密集点云进行重构。最后利用泊松重建对服装表面细节进行复原。结果表明,在服装单眼多视角三维重建过程中,加入案例分割和双约束可以有效地降低点云噪声,加快重建速度。该方法还可以在三维模型重建过程中还原服装的表面细节。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research and Implementation of 3D Reconstruction Algorithm for Multi-angle Monocular Garment Image
In order to reduce the difficulty in constructing garment modeling and improve the construction efficiency of garment modeling. In this paper, a method of garment 3D reconstruction based on monocular and multi view is proposed. Firstly, the garment image sequence is obtained, and then the contour information including garment part is obtained by instantiating and segmenting the garment image sequence. The feature points and matching of each image are extracted by SIFT algorithm, and the error matching is eliminated by adding double constraints. Then, sparse point cloud and dense point cloud are reconstructed. Finally, Poisson reconstruction is used to restore the surface details of clothing. The results show that the point cloud noise can be effectively reduced and the reconstruction speed can be accelerated by adding case segmentation and double constraints in the process of garment monocular multi view garment 3D reconstruction. This method can also restore the surface details of clothing in the process of 3D model reconstruction.
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