Efficient Use of Geometric Constraints for Sliding-Window Object Detection in Video

  • Patrick Sudowe
  • Bastian Leibe
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6962)


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.


Object Detection Ground Plane Geometric Constraint Pedestrian Detection Scene Geometry 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Patrick Sudowe
    • 1
  • Bastian Leibe
    • 1
  1. 1.UMIC Research CentreRWTH Aachen UniversityGermany

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