Shadow Removal from Single RGB-D Images

Yao Xiao, Efstratios Tsougenis, Chi-Keung Tang; Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014, pp. 3011-3018

Abstract


We present the first automatic method to remove shadows from single RGB-D images. Using normal cues directly derived from depth, we can remove hard and soft shadows while preserving surface texture and shading. Our key assumption is: pixels with similar normals, spatial locations and chromaticity should have similar colors. A modified nonlocal matching is used to compute a shadow confidence map that localizes well hard shadow boundary, thus handling hard and soft shadows within the same framework. We compare our results produced using state-of-the-art shadow removal on single RGB images, and intrinsic image decomposition on standard RGB-D datasets.

Related Material


[pdf]
[bibtex]
@InProceedings{Xiao_2014_CVPR,
author = {Xiao, Yao and Tsougenis, Efstratios and Tang, Chi-Keung},
title = {Shadow Removal from Single RGB-D Images},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2014}
}