Efficient use of geometric constraints for sliding-window object detection in video

  • Authors:
  • Patrick Sudowe;Bastian Leibe

  • Affiliations:
  • UMIC Research Centre, RWTH Aachen University, Germany;UMIC Research Centre, RWTH Aachen University, Germany

  • Venue:
  • ICVS'11 Proceedings of the 8th international conference on Computer vision systems
  • Year:
  • 2011

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Abstract

We systematically investigate how geometric constraints can be used for efficient sliding-window object detection. Starting with a general characterization of the space of sliding-window locations that correspond to geometrically valid object detections, we derive a general algorithm for incorporating ground plane constraints directly into the detector computation. Our approach is indifferent to the choice of detection algorithm and can be applied in a wide range of scenarios. In particular, it allows to effortlessly combine multiple different detectors and to automatically compute regions-of-interest for each of them. We demonstrate its potential in a fast CUDA implementation of the HOG detector and show that our algorithm enables a factor 2-4 speed improvement on top of all other optimizations.