Hefei Ling1, Jia Wu1, Ping Li1,*, Jialie Shen2
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1041-1054, 2019, DOI:10.32604/cmc.2019.05605
Abstract Gait recognition is a complicated task due to the existence of co-factors like carrying conditions, clothing, viewpoints, and surfaces which change the appearance of gait more or less. Among those co-factors, clothing analysis is the most challenging one in the area. Conventional methods which are proposed for clothing invariant gait recognition show the body parts and the underlying relationships from them are important for gait recognition. Fortunately, attention mechanism shows dramatic performance for highlighting discriminative regions. Meanwhile, latent semantic analysis is known for the ability of capturing latent semantic variables to represent the underlying attributes and capturing the relationships from… More >
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