Surface Area Analysis for People Number Estimation

Hiroyuki Arai, Naoki Ito, Yukinobu Taniguchi

Abstract

An important property of surface areas of objects as observed by a calibrated monocular camera is introduced; also improved techniques to apply the property to people number estimation are proposed. Standard surface area (SSA) is defined as the surface area of the reverse projection of an image-pixel onto a plane at specific height in the real world. SSA is calculated for each pixel according to camera calibration parameters. When the target object is bound to a certain plane, for example the floor plane, the sum of SSA along with the foreground pixels of one target object becomes constant. Therefore, simple foreground detection and SSA summation yield the number of target objects. This basic idea was proposed in a prior article, but there were two major limitations. One is that the original model could not be applied to the area directly below the camera. The other is that the silhouette of the target object was limited to a simple rectangle. In this paper we propose improved techniques that remove the limitations. Slant silhouette analysis removes the first limitation, and silhouette decomposition the second. The validity and the effectiveness of the techniques are confirmed by experiments.

References

  1. Antonini, G. and Thiran, J. (2006). Counting pedestrians in video sequences using trajectory clustering. IEEE Transactions on Circuits and Systems for Video Technology, 16(issue 8):1008-1020.
  2. Arai, H., Miyagawa, I., Koike, H., and Haseyama, M. (2009). Estimating number of people using calibrated monocular camera based on geometrical analysis of surface area. IEICE Transactions, 92-A(8):1932- 1938.
  3. Cho, S.-Y., Chow, T., and Leung, C.-T. (1999). A neuralbased crowd estimation by hybrid global learning algorithm. IEEE Transactions on Systems, Man, and Cybernetics, 29(PartB)(issue 4):535-541.
  4. Kong, D., Gray, D., and Tao, H. (2006). A viewpoint invariant approach for crowd counting. Proceedings of the 18th International Conference on Pattern Recognition, 03:1187-1190.
  5. Marana, A., Costa, L., Lotufo, R., and Velastin, S. (1998). On the efficacy of texture analysis for crowd monitoring. Proceedings of the International Symposium on Computer Graphics, Image Processing, 6:3521-3524.
  6. Min, L., Zhaoxiang, Z., Kaiqi, H., and Tieniu, T. (2008). Estimating the number of people in crowded scenes by mid based foreground segmentation and headshoulder detection. International Conference on Pattern Recognition(ICPR 2008), pages 1-4.
  7. Rabaud, V. and Belongie, S. (2006). Counting crowded moving objects. Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1:705-711.
  8. Sheng-Fuu Lin, J.-Y. C. and Chao, H.-X. (2001). Estimation of number of people in crowded scenes using perspective transformation. IEEE Transactions on Man and Cybernetics, 31(PartA)(Issue 6):645-654.
  9. Sidla, O., Lypetskyy, Y., Brandle, N., and Seer, S. (2006). Pedestrian detection and tracking for counting applications in crowded situations. Proceedings of the IEEE International Conference on Video and Signal Based Surveillance(AVSS06), pages 70-.
  10. Wen, Q., JIA, C., Yu, Y., Chen, G., Yu, Z., and Zhou, C. (2011). People number estimation in the crowded scenes using texture analysis based on gabor filter. Journal of Computational Information Systems, 7:11:3754-3763.
  11. Zhao, T., Nevatia, R., and Wu, B. (2007). Segmentation and tracking of multiple humans in crowded environments. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(7):1198-1211.
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Paper Citation


in Harvard Style

Arai H., Ito N. and Taniguchi Y. (2014). Surface Area Analysis for People Number Estimation . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-004-8, pages 86-93. DOI: 10.5220/0004687000860093


in Bibtex Style

@conference{visapp14,
author={Hiroyuki Arai and Naoki Ito and Yukinobu Taniguchi},
title={Surface Area Analysis for People Number Estimation},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={86-93},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004687000860093},
isbn={978-989-758-004-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2014)
TI - Surface Area Analysis for People Number Estimation
SN - 978-989-758-004-8
AU - Arai H.
AU - Ito N.
AU - Taniguchi Y.
PY - 2014
SP - 86
EP - 93
DO - 10.5220/0004687000860093