Shading-Based Shape Refinement of RGB-D Images

Lap-Fai Yu, Sai-Kit Yeung, Yu-Wing Tai, Stephen Lin; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013, pp. 1415-1422


We present a shading-based shape refinement algorithm which uses a noisy, incomplete depth map from Kinect to help resolve ambiguities in shape-from-shading. In our framework, the partial depth information is used to overcome bas-relief ambiguity in normals estimation, as well as to assist in recovering relative albedos, which are needed to reliably estimate the lighting environment and to separate shading from albedo. This refinement of surface normals using a noisy depth map leads to high-quality 3D surfaces. The effectiveness of our algorithm is demonstrated through several challenging real-world examples.

Related Material

author = {Yu, Lap-Fai and Yeung, Sai-Kit and Tai, Yu-Wing and Lin, Stephen},
title = {Shading-Based Shape Refinement of RGB-D Images},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2013}