Shading-based Shape Refinement of RGB-D Images

被引:79
作者
Yu, Lap-Fai [1 ]
Yeung, Sai-Kit [2 ]
Tai, Yu-Wing [3 ]
Lin, Stephen [4 ]
机构
[1] Univ Calif Los Angeles, Los Angeles, CA 90095 USA
[2] Singapore Univ Technol & Design, Singapore, Singapore
[3] Korea Adv Inst Sci & Technol, Seoul, South Korea
[4] Microsoft Res Asia, Seoul, South Korea
来源
2013 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR) | 2013年
基金
新加坡国家研究基金会;
关键词
D O I
10.1109/CVPR.2013.186
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:1415 / 1422
页数:8
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