Kinect Shadow Detection and Classification

被引:6
作者
Deng, Teng [1 ]
Li, Hui [1 ]
Cai, Jianfei [1 ]
Cham, Tat-Jen [1 ]
Fuchs, Henry [2 ]
机构
[1] Nanyang Technol Univ, Nanyang, Singapore
[2] Univ N Carolina, Chapel Hill, NC USA
来源
2013 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW) | 2013年
关键词
SEGMENTATION;
D O I
10.1109/ICCVW.2013.97
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:708 / 713
页数:6
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