GPU-Accelerated Human Detection Using Fast Directional Chamfer Matching

@article{Schreiber2013GPUAcceleratedHD,
  title={GPU-Accelerated Human Detection Using Fast Directional Chamfer Matching},
  author={David Schreiber and Csaba Beleznai and Michael Rauter},
  journal={2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops},
  year={2013},
  pages={614-621}
}
We present a GPU-accelerated, real-time and practical, pedestrian detection system, which efficiently computes pedestrian-specific shape and motion cues and combines them in a probabilistic manner to infer the location and occlusion status of pedestrians viewed by a stationary camera. The articulated pedestrian shape is approximated by a mean contour template, where template matching against an incoming image is carried out using line integral based, Fast Directional Chamfer Matching, employing… CONTINUE READING

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