Real-time Gender Classification from Human Gait for Arbitrary View Angles

  title={Real-time Gender Classification from Human Gait for Arbitrary View Angles},
  author={Ping-Chieh Chang and Ming-Chun Tien and Ja-Ling Wu and Chuan-Shen Hu},
  journal={2009 11th IEEE International Symposium on Multimedia},
In this paper, we investigate an important but understudied problem, gender classification from human gaits. And we have proved the ability of using GEI (Gait Energy Image) as a representation of human gait for arbitrary view angles. Using GEI as a discriminative feature, we construct angle classifiers and gender classifiers from different approaches. Experiments show that our system achieved a good performance in real-time and is able to be applied to real-world application. 
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