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Paired Regions for Shadow Detection and Removal
Dec. 2013 (vol. 35 no. 12)
pp. 2956-2967
Ruiqi Guo, Dept. of Comput. Sci., Univ. of Illinois at Urbana Champaign, Urbana, IL, USA
Qieyun Dai, Dept. of Comput. Sci., Univ. of Illinois at Urbana Champaign, Urbana, IL, USA
Derek Hoiem, Dept. of Comput. Sci., Univ. of Illinois at Urbana Champaign, Urbana, IL, USA
In this paper, we address the problem of shadow detection and removal from single images of natural scenes. Differently 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 nonshadow 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 Zhu et al. . In addition, we created a new dataset with shadow-free ground truth images, which provides a quantitative basis for evaluating shadow removal. We study the effectiveness of features for both unary and pairwise classification.
Index Terms:
object detection,graph theory,image classification,image enhancement,natural scenes,shadow detection,unary classification,shadow-free ground truth image,lighting model,shadow-free image,image matting,graph-cut,pairwise classification,relative illumination,region-based approach,edge information,pixel information,natural scene,shadow removal,Lighting,Shadow detection,Image color analysis,Image edge detection,Histograms,enhancement,Shadow detection,region classification,shadow removal
Citation:
Ruiqi Guo, Qieyun Dai, Derek Hoiem, "Paired Regions for Shadow Detection and Removal," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 35, no. 12, pp. 2956-2967, Dec. 2013, doi:10.1109/TPAMI.2012.214
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