Gait or an individuals manner of walking, is one approach for recognizing people at a distance. Studies in psychophysics and medicine indicate that humans can recognize people by their gait and have found twenty-four different components to gait that taken together make it a unique signature. Besides not requiring close sensor contact, gait also does not necessarily require a cooperative subject. Using video data of people walking in different scenarios and environmental conditions we develop and test an algorithm that uses shape and motion to identify people from their gait. The algorithm uses dynamic time warping to match stored templates against an unknown sequence of silhouettes extracted from a person walking. While results under similar constraints and conditions are very good, the algorithm quickly degrades with varying conditions such as surface and clothing.


    Access

    Access via TIB

    Check availability in my library


    Export, share and cite



    Gait recognition using a few gait frames.

    Yao, L / Kusakunniran, W / Wu, Q et al. | BASE | 2021

    Free access

    Multi-gait recognition using hypergraph partition

    Chen, X. / Xu, J. / Weng, J. | British Library Online Contents | 2017


    Improved Human Gait Recognition

    Rida, Imad / Bouridane, Ahmed / Marcialis, Gian Luca et al. | British Library Conference Proceedings | 2015


    Gait recognition by fluctuations

    Aqmar, M. R. / Fujihara, Y. / Makihara, Y. et al. | British Library Online Contents | 2014


    Investigation of New Gait Representations for Improving Gait Recognition

    Chirawat Wattanapanich / Hong Wei | BASE | 2017

    Free access