Abstract

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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