Rapid and robust human detection and tracking based on omega-shape features

@article{Li2009RapidAR,
  title={Rapid and robust human detection and tracking based on omega-shape features},
  author={Min Li and Zhaoxiang Zhang and Kaiqi Huang and Tieniu Tan},
  journal={2009 16th IEEE International Conference on Image Processing (ICIP)},
  year={2009},
  pages={2545-2548}
}
  • Min Li, Zhaoxiang Zhang, +1 author T. Tan
  • Published 7 November 2009
  • Computer Science
  • 2009 16th IEEE International Conference on Image Processing (ICIP)
This paper proposes a novel method for rapid and robust human detection and tracking based on the omega-shape features of people's head-shoulder parts. There are two modules in this method. In the first module, a Viola-Jones type classifier and a local HOG (Histograms of Oriented Gradients) feature based AdaBoost classifier are combined to detect head-shoulders rapidly and effectively. Then, in the second module, each detected head-shoulder is tracked by a particle filter tracker using local… 
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