Kinect Shadow Detection and Classification

Teng Deng, Hui Li, Jianfei Cai, Tat-Jen Cham, Henry Fuchs; Proceedings of the IEEE International Conference on Computer Vision (ICCV) Workshops, 2013, pp. 708-713

Abstract


Kinect depth maps often contain missing data, or "holes", for various reasons. Most existing Kinect-related research treat these holes as artifacts and try to minimize them as much as possible. In this paper, we advocate a totally different idea turning Kinect holes into useful information. In particular, we are interested in the unique type of holes that are caused by occlusion of the Kinect's structured light, resulting in shadows and loss of depth acquisition. We propose a robust detection scheme to detect and classify different types of shadows based on their distinct local shadow patterns as determined from geometric analysis, without assumption on object geometry. Experimental results demonstrate that the proposed scheme can achieve very accurate shadow detection. We also demonstrate the usefulness of the extracted shadow information by successfully applying it for automatic foreground segmentation.

Related Material


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[bibtex]
@InProceedings{Deng_2013_ICCV_Workshops,
author = {Teng Deng and Hui Li and Jianfei Cai and Tat-Jen Cham and Henry Fuchs},
title = {Kinect Shadow Detection and Classification},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV) Workshops},
month = {June},
year = {2013}
}