A Complexity Measure of Gait Perception

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• 作者：Javier Ortells Lorenzo (19)
  Raúl Martín-Félez (19)
  Ramón A. Mollineda Cárdenas (19)
  
• 关键词：gait complexity ; non ; stationary process ; transfer learning
• 刊名：Lecture Notes in Computer Science
• 出版年：2013
• 出版时间：2013
• 年：2013
• 卷：7887
• 期：1
• 页码：500-508
• 全文大小：459KB
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• 作者单位：Javier Ortells Lorenzo (19)
  Raúl Martín-Félez (19)
  Ramón A. Mollineda Cárdenas (19)
  
  19. Institute of New Imaging Technologies, Universitat Jaume I, 12071, Castelló, Spain
  
• ISSN：1611-3349

文摘

This paper proposes a probabilistic method for measuring and characterizing the complexity of gait samples represented by the well-known Gait Energy Image (GEI). The term complexity is here used to denote how singular (far from normality) a GEI is and how challenging might be its classification. We believe that a robust complexity index computed on a new gait sample could help to judge the reliability of the prediction given by a classifier. Experiments to assess the validity of the proposed measure and how it correlates with gait recognition effectiveness were conducted on two public databases covering both indoor and outdoor scenarios and variable covariate conditions.