Computer Vision @ LEMS

This paper introduces a novel method for surface reconstruction using the depth discontinuity information captured by a multi-flash camera while the object moves along a known trajectory. Experimental results based on turntable sequences are presented. By observing the visual motion of depth discontinuities, surface points are accurately reconstructed - including many located deep inside concavities. The method extends well-established differential and global shape-from-silhouette surface reconstruction techniques by incorporating the significant additional information encoded in the depth discontinuities. The reconstruction method uses an implicit form of the epipolar parameterization and directly estimates point locations and corresponding surface normals on the surface of the object using a local temporal neighborhood of the depth discontinuities. Outliers, which correspond to the ill-conditioned cases of the reconstruction equations, are easily detected and removed by back-projection. Gaps resulting from curvature- dependent sampling and shallow concavities are filled by fitting an implicit surface to the oriented point cloud's point locations and normal vectors.