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Single-Image Shadow Detection and Removal using Paired Regions

8 years 5 months ago
Single-Image Shadow Detection and Removal using Paired Regions
In this paper, we address the problem of shadow detection and removal from single images of natural scenes. Different from traditional methods that explore pixel or edge information, we employ a region based approach. In addition to considering individual regions separately, we predict relative illumination conditions between segmented regions from their appearances and perform pairwise classification based on such information. Classification results are used to build a graph of segments, and graph-cut is used to solve the labeling of shadow and non-shadow regions. Detection results are later refined by image matting, and the shadow free image is recovered by relighting each pixel based on our lighting model. We evaluate our method on the shadow detection dataset in [19]. In addition, we created a new dataset with shadow-free ground truth images, which provides a quantitative basis for evaluating shadow removal.
Ruiqi Guo, Qieyun Dai, Derek Hoiem
Added 30 Apr 2011
Updated 30 Apr 2011
Type Journal
Year 2011
Where CVPR
Authors Ruiqi Guo, Qieyun Dai, Derek Hoiem
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