Sparsity Driven People Localization with a Heterogeneous Network of Cameras

@article{Alahi2010SparsityDP,
  title={Sparsity Driven People Localization with a Heterogeneous Network of Cameras},
  author={Alexandre Alahi and Laurent Jacques and Yannick Boursier and Pierre Vandergheynst},
  journal={Journal of Mathematical Imaging and Vision},
  year={2010},
  volume={41},
  pages={39-58}
}
This paper addresses the problem of localizing people in low and high density crowds with a network of heterogeneous cameras. The problem is recast as a linear inverse problem. It relies on deducing the discretized occupancy vector of people on the ground, from the noisy binary silhouettes observed as foreground pixels in each camera. This inverse problem is regularized by imposing a sparse occupancy vector, i.e., made of few non-zero elements, while a particular dictionary of silhouettes… CONTINUE READING
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Monotone operator splitting for fast sparse solutions of inverse problems

  • M. J. Fadili, J. L. Starck
  • SIAM J. Imaging Sci., – 2006
  • 2009
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