Complete Multi-View Reconstruction of Dynamic Scenes from Probabilistic Fusion of Narrow and Wide Baseline Stereo

This paper presents a novel approach to achieve accurate and complete multi-view reconstruction of dynamic scenes (or 3D videos). 3D videos consist in sequences of 3D models in motion captured by a surrounding set of video cameras. To date 3D videos are reconstructed using multiview wide baseline stereo (MVS) reconstruction techniques. However it is still tedious to solve stereo correspondence problems: reconstruction accuracy falls when stereo photoconsistency is weak, and completeness is limited by selfocclusions. Most MVS techniques were indeed designed to deal with static objects in a controlled environment and therefore cannot solve these issues. Hence we propose to take advantage of the image content stability provided by each single-view video to recover any surface regions visible by at least one camera. In particular we present an original probabilistic framework to derive and predict the true surface of models. We propose to fuse multi-view structurefrom- motion with robust...

• Type: Conference
• Year: 2009
• Where: ICCV
• Authors: Tony Tung, Shohei Nobuhara, Takashi Matsuyama
• Keywords: 3D Reconstruction, 3D Video, Computer Vision, ICCV 2009, Probalistic Fusion, SFM, Stereo