关键词: 立体重建, MFPMVS算法, PMVS算法, 特征匹配

Abstract: 3D reconstruction techniques based on images directly obtain 3D model information from multiple images. This kind of methods are with higher automaticity, moreover, they do not need any prior information and special hardware. But for Chinese ancient architectures with exquisite carving or the large outdoor scenes with non-parallel shooting, reconstruction results of existing 3D reconstruction techniques based on images may be not always promising because the details about modeling object are often missed or diffused. This paper considers comprehensively the multiple features of models such as lighting, texture, shadows and concavity, and proposes a novel algorithm for 3D reconstruction named MFPMVS (patch with multiple features based multi-view stereopsis) based on candidate feature points mapping strategy and reliability sorting on initial cloud points. The experimental results show that, compared with the classical PMVS (patch based multi-view stereopsis) algorithm, the proposed MFPMVS algorithm can obtain more 3D point cloud, and the details of strong concavity model are more delicate. Meanwhile, the loopholes of the reconstruction model with upward-shooting can be significantly reduced, and the edge information is more complete. More importantly, the proposed algorithm can rebuild the 3D model of the object more stably and robustly, which means the high practicability.

Key words: 3D reconstruction, patch with multiple features based multi-view stereopsis (MFPMVS), patch based multi-view stereopsis (PMVS), feature matching