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    Motion-Based Gait Recognition for Recognizing People in Traditional Gulf Clothing

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    12-Motion-Based Gait Recognition for Recognizing People in Traditional Gulf Clothing.pdf (848.6Kb)
    Date
    2019
    Author
    Towheed, Mohammad Asif
    Kiyani, Wasif
    Ummar, Mumtaz
    Shanableh, Tamer
    Dhou, Salam
    Advisor(s)
    Unknown advisor
    Type
    Peer-Reviewed
    Article
    Published version
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    Abstract
    Gait recognition is gaining popularity as it can recognize people in a non-intrusive and a non-contact manner. However, gait recognition is known for its susceptibility to clothing conditions. In this paper, we propose a solution specific to clothing conditions in the Gulf region where Abaya and Kandura are considered traditional clothing. The paper proposes a solution capable of training users based on traditional clothing and recognizing them in Western style clothing and vice-a-versa. The solution uses depth imaging, optical flow, accumulated motion and Discrete Cosine Transformation (DCT). Motion is calculated from consecutive images where the magnitudes and phases of motion vectors are accumulated into separate matrices. DCT and zonal coding is then applied to these matrices to form one concise feature vector that represents a walk. Experimental results, with 38 participants, showed that the proposed method is suitable for gait recognizing with such clothing constraints. The average classification accuracy is 88%. In comparison to an existing method, it is shown that the proposed method results in much more accurate recognition results yet at a higher computational cost.
    DSpace URI
    http://hdl.handle.net/11073/21365
    External URI
    https://doi.org/10.1109/AICCSA47632.2019.9035284
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