Rattanapitak, Wirat

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Rattanapitak, Wirat
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wirat.ra@kmitl.ac.th

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    Item type:Publication,
    Human height estimation using visual geometry and feature learning
    (2021-01-01)
    Dokthurian, Siriporn
    ;
    Rattanapitak, Wirat
    ;
    Wangsiripitak, Somkiat
    Many existing video surveillance systems use human characteristics like face, height, and gait to identify a person. This paper proposes a human height estimation approach using visual geometry and feature learning that makes an estimate from a video clip of a person. An experiment was conducted to evaluate the performance of the approach. The approach achieved an average percentage final height estimate of 100.59 % (actual height = 100%), better than a previously reported estimate of 98.8% in the literature achieved by another approach. A successful further development of this approach would directly benefit forensic science investigators.