3D reconstruction using silhouettes from unordered viewpoints

In this paper, we present a novel approach for reconstructing an object surface from its silhouettes. The proposed approach directly estimates the differential structure of the surface, and results in a higher accuracy than existing volumetric approaches for object reconstruction. Compared with other existing differential approaches, our approach produces relatively complete 3D models similar to volumetric approaches, with the topology conforming to what is observed from the silhouettes. In addition, the method neither assumes nor depends on the spatial order of viewpoints. Experimental results on both synthetic and real world data are presented, and comparison is made with other existing approaches to demonstrate the superiority of the proposed approach.