Kinect shadow detection and classification

Teng Deng, Hui Li, Jianfei Cai, Tat Jen Cham, Henry Fuchs

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

10 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationProceedings - 2013 IEEE International Conference on Computer Vision Workshops, ICCVW 2013
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages6
ISBN (Print)9781479930227
Publication statusPublished - 2013
Externally publishedYes
EventIEEE International Conference on Computer Vision Workshops 2013 - Sydney, Australia
Duration: 1 Dec 20138 Dec 2013
Conference number: 14th


ConferenceIEEE International Conference on Computer Vision Workshops 2013
Abbreviated titleICCVW 2013

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