Semantic Attribute Classification Related to Gait

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 736)

Abstract

Human gait, as a behavioral biometric, has recently gained significant attention from computer vision researchers. But there are some challenges which hamper using this biometric in real applications. Among these challenges is clothing variations and carrying objects which influence on its accuracy. In this paper, we propose a semantic classification based method in order to deal with such challenges. Different predictive models are elaborated in order to determine the most relevant model for this task. Experimental results on CASIA-B gait database show the performance of our proposed method.

Keywords

Pedestrian analysis Semantic attributes Classification 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.MIRACL Laboratory, ENISUniversity of SfaxSfaxTunisia
  2. 2.MIRACL Laboratory, FSSUniversity of SfaxSfaxTunisia

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