DETECTING PERSONS USING HOUGH CIRCLE TRANSFORM IN SURVEILLANCE VIDEO

Hong Liu, Yueliang Qian, Shouxun Lin

Abstract

Robust person detection in real-world images is interesting and important for a variety of applications, such as visual surveillance. We address the task of detecting persons in elevator surveillance scenes in this paper. To get more passengers in the lift car, the camera usually installed at the corner of ceiling. However, the high and space of lift car are limited, which makes person occluded by each other or some parts of body invisible in captured images. In this paper, we propose a novel approach to detect head contours, which includes three main steps: pre-processing, head contour detection and post-processing. Hough circle transform is adopted in the second stage, which is robust to discontinuous boundaries in circle detection. Proposed pre-processing and post-processing methods are efficient to remove false alarms on background or body part. Experimental results show our proposed approach is time saving and has better person detection results than some other methods.

References

  1. Leibe, B., Seemann, E., Schiele, B., 2005, Pedestrian Detection in Crowded Scenes. In Proc. Computer Vision and Pattern Recognition, vol.1, 878-885.
  2. Gavrila, D., 2000, Pedestrian detection from a moving vehicle. In Proc. 6th European Conf. Computer Vision, Dublin, Ireland, vol.2, 37-49.
  3. Giebel, J., Gavrila, D.M., 2004, A Bayesian framework for multi-cue 3d object tracking. In Proc. 8th European Conf. Computer Vision, Prague, Czech Republic, 241- 252.
  4. Schmid, C., Mikolajczyk, K. and Zisserman, A., 2004, Human detection based on a probabilistic assembly of robust part detectors. In Proc. 8th European Conf. Computer Vision, Prague,Czech Republic, vol.1, 69- 82.
  5. Nakajima, C., Pontil, M., Heisele, B.and Poggio, T., 2000, People recognition in image sequences by supervised learning. In MIT AI Memo.
  6. Viola. P. and Jones. M., 2001, Rapid object detection using a boosted cascade of simple features. In IEEE Conference on Computer Vision and Pattern Recognition.
  7. Zhang, X.W., Sexton, G., 1995, A new method for pedestrian counting. Proceedings of the Fifth International Conference on Image Processing and its Applications, 208- 212.
  8. Yuen, H. K., Proncen, Illingworth, J., Kittler, J., 1990, Comparative Study of Hough Transform Methods for Circle Finding. Image and Vision Computing, Vol.8, No.1, 71-77.
  9. Kimme, C., Ballard, D. H. and Sklansky, J., 1975, Finding circles by an array of accumulators. Communications of the Association for Computing Machinery, vol.18, 120-122.
  10. Bradski, G., Kaebler, A., 2008, Learing Opencv: Computer vision with the Opencv library. Publisher: O'Reilly Media.
Download


Paper Citation


in Harvard Style

Liu H., Qian Y. and Lin S. (2010). DETECTING PERSONS USING HOUGH CIRCLE TRANSFORM IN SURVEILLANCE VIDEO . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2010) ISBN 978-989-674-029-0, pages 267-270. DOI: 10.5220/0002856002670270


in Bibtex Style

@conference{visapp10,
author={Hong Liu and Yueliang Qian and Shouxun Lin},
title={DETECTING PERSONS USING HOUGH CIRCLE TRANSFORM IN SURVEILLANCE VIDEO},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2010)},
year={2010},
pages={267-270},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002856002670270},
isbn={978-989-674-029-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2010)
TI - DETECTING PERSONS USING HOUGH CIRCLE TRANSFORM IN SURVEILLANCE VIDEO
SN - 978-989-674-029-0
AU - Liu H.
AU - Qian Y.
AU - Lin S.
PY - 2010
SP - 267
EP - 270
DO - 10.5220/0002856002670270