Abstract
3D reconstruction systems are promoted by developments of both computer hardware and computing technologies. They still remain problems like high expense, low efficiency and inaccuracy. Especially for large-scale scenes, lack of full use of multi-scale depth information will cause blurring and irreal reconstruction results. To solve this problem, we construct the structure of hierarchical signed distance field (H-SDF) and design an improved marching tetrahedra algorithm for multi-scale depth map fusion. In addition, to improve efficiency, we also propose a two-phase search strategy in image feature matching: the bag-of-features model (BOF) is adopted in a coarse search to narrow search scope and then the SIFT descriptor is used in exact matching to pick reconstruction image points. Experiment results indicate that coarse search makes matching time shorter; using the H-SDF to fuse multi-scale depth maps, and isosurface extraction with improved marching tetrahedra algorithm can improve visual effect.
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