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    A novel human detection approach based on Depth map via Kinect

    Access Status
    Fulltext not available
    Authors
    Shen, Y.
    Hao, Z.
    Wang, P.
    Ma, S.
    Liu, Wan-Quan
    Date
    2013
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Shen, Yujie and Hao, Zhonghua and Wang, Pengfei and Ma, Shiwei and Liu, Wanquan. 2013. A novel human detection approach based on Depth map via Kinect, in IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Jun 23-28 2013, pp. 535-541. Portland, Oregan, USA: IEEE.
    Source Title
    2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops
    Source Conference
    CVPRW 2013
    DOI
    10.1109/CVPRW.2013.85
    URI
    http://hdl.handle.net/20.500.11937/6096
    Collection
    • Curtin Research Publications
    Abstract

    In this paper, a new method of human detection based on depth map from 3D sensor Kinect is proposed. First, the pixel filtering and context filtering are employed to roughly repair defects on the depth map due to information inaccuracy captured by Kinect. Second, a dataset consisting of depth maps with various indoor human poses is constructed as benchmark. Finally, by introducing Kirsch mask and three-value codes to Local Binary Pattern, a novel Local Ternary Direction Pattern (LTDP) feature descriptor is extracted and is used for human detection with SVM as classifier. The performance for the proposed approach is evaluated and compared with other five existing feature descriptors using the same SVM classifier. Experiment results manifest the effectiveness of the proposed approach.

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