Title :
Shape reconstruction with globally-optimized surface point selection
Author :
Ukita, Norimichi ; Matsuda, Keisuke ; Hagita, Norihiro
Abstract :
This paper proposes a method for reconstructing accurate 3D surface points. To this end, robust and dense reconstruction with Shape-from-Silhouettes (SfS) and accurate multiview stereo are integrated. Unlike gradual shape shrinking and/or bruteforce large space search by existing space carving approaches, our method obtains 3D points by SfS and stereo independently, and then selects correct ones from them. The point selection is achieved in accordance with spatial consistency and smoothness of 3D point coordinates and normals. The globally optimized points are selected by graph-cuts. Experimental results demonstrate that our method outperforms existing approaches.
Keywords :
graph theory; image reconstruction; optimisation; stereo image processing; 3D point coordinates; 3D point normals; 3D surface point reconstruction; SfS; globally optimized surface point selection; graph-cuts; multiview stereo; shape reconstruction; shape-from-silhouettes; spatial consistency; Image reconstruction; Optimization; Shape; Stereo vision; Surface reconstruction; Surface treatment;
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Print_ISBN :
978-1-4673-2216-4