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Efficient multi-hypothesis multi-human 3D tracking in crowded scenes

  • US 8,098,891 B2
  • Filed: 11/24/2008
  • Issued: 01/17/2012
  • Est. Priority Date: 11/29/2007
  • Status: Active Grant
First Claim
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1. A method to perform multi-human three dimensional (3D) tracking, comprising:

  • for each single view, providing two dimensional (2D) human detection candidates from a camera to a 2D tracking module wherein a Convolutional Neural Network (CNN) generates the 2D human detection candidates;

    a. independently performing 2D tracking in each 2D tracking module and reporting promising 2D tracking hypotheses to a 3D tracking module;

    b. selecting trajectories from the 2D tracking modules to generate 3D tracking hypotheses; and

    c. determining a difference score between the detection and the trajectory as a weighted sum of appearance, location, blob size, and orientation.

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