A Framework for Ultra High Resolution 3D Imaging

We present an imaging framework to acquire 3D surface scans at ultra high-resolutions (exceeding 600 samples per mm2 ). Our approach couples a standard structured-light setup and photometric stereo using a large-format ultrahigh-resolution camera. While previous approaches have employed similar hybrid imaging systems to fuse positional data with surface normals, what is unique to our approach is the significant asymmetry in the resolution between the low-resolution geometry and the ultra-high-resolution surface normals. To deal with these resolution differences, we propose a multi-resolution surface reconstruction scheme that propagates the low-resolution geometric constraints through the different frequency bands while gradually fusing in the high-resolution photometric stereo data. In addition, to deal with the ultra-high-resolution images, our surface reconstruction is performed in a patch-wise fashion and additional boundary constraints are used to ensure patch coherence. Based on...

• Type: Conference
• Year: 2010
• Where: CVPR
• Authors: Zheng Lu, Yu-Wing Tai, Moshe Ben-Ezra, Michael Brown
• Keywords: Computer Vision, CVPR 2010, Photometric Stereo, Surface Normals, Surface Reconstruction