PEOPLE DETECTION AND RE-IDENTIFICATION FOR MULTI SURVEILLANCE CAMERAS

Etienne Corvee, Slawomir Bak, François Brémond

Abstract

Re-identifying people in a network of non overlapping cameras requires people to be accurately detected and tracked in order to build a strong visual signature of people appearances. Traditional surveillance cameras do not provide high enough image resolution to iris recognition algorithms. State of the art face recognition can not be easily applied to surveillance videos as people need to be facing the camera at a close range. The different lighting environment contained in each camera scene and the strong illumination variability occurring as people walk throughout a scene induce great variability in their appearance. In addition, people images occlud each other onto the image plane making people detection difficult to achieve. We propose a novel simplified Local Binary Pattern features to detect people, head and faces. A Mean Riemannian Covariance Grid (MRCG) is used to model appearance of tracked people to obtain highly discriminative human signature. The methods are evaluated and compared with the state of the art algorithms. We have created a new dataset from a network of 2 cameras showing the usefulness of our system to detect, track and re-identify people using appearance and face features.

References

  1. Adam, A., Rivlin, E., and Shimshoni, I. (2006). Robust fragment-based tracking using integral histogram. In Computer Vision and Pattern Recognition - CVPR.
  2. Avanzi, A., Bremond, F., and Thonnat, M. (2001). Tracking multiple individuals for video communication. In In IEEE Proc. of International Conference on Image Processing, Thessaloniki (Greece).
  3. Bak, S., Corvee, E., Bremond, F., and Thonnat, M. (2010a). Person re-identification using haar-based and dcdbased signature. In 2nd Workshop on AMMCSS.
  4. Bak, S., Corvee, E., Bremond, F., and Thonnat, M. (2010b). Person re-identification using spatial covariance regions of human body parts. In AVSS.
  5. Bak, S., Corvee, E., Bremond, F., and Thonnat, M. (2011). Multiple-shot human re-identification by mean riemannian covariance grid. In AVSS.
  6. Bazzani, L., Cristani, M., Perina, A., Farenzena, M., and Murino, V. (2010). Multiple-shot person reidentification by hpe signature. In ICPR, pages 1413- 1416.
  7. Dalal, N. and Triggs, B. (2005a). Histograms of Oriented Gradients for Human Detection. In Computer Vision and Pattern Recognition - CVPR.
  8. Dalal, N. and Triggs, B. (2005b). Histograms of oriented gradients for human detection. In CVPR, pages 886- 893.
  9. Dollar, P., Wojek, C., Schiele, B., and Perona, P. (2009). Pedestrian detection: a benchmark. In CVPR.
  10. Farenzena, M., Bazzani, L., Perina, A., Murino, V., and Cristani, M. (2010). Person re-identification by symmetry-driven accumulation of local features. In CVPR, pages 2360-2367.
  11. Gallagher, A. C. and Chen, T. (2008). Clothing cosegmentation for recognizing people. In CVPR, pages 1-8.
  12. Gheissari, N., Sebastian, T. B., and Hartley, R. (2006). Person reidentification using spatiotemporal appearance. In CVPR, pages 1528-1535.
  13. Gray, D., Brennan, S., and Tao, H. (2007). Evaluating Appearance Models for Recognition, Reacquisition, and Tracking. PETS.
  14. Gray, D. and Tao, H. (2008). Viewpoint invariant pedestrian recognition with an ensemble of localized features. In ECCV, pages 262-275.
  15. Huang, C. and Nevatia, R. (2010). High performance object detection by collaborative learning of joint ranking of granules features. IEEE - CVPR 2010.
  16. Hussein, M., Porikli, F., and Davis, L. (2009). Object detection via boosted deformable features. IEEE International Conference on Image Processing (ICIP).
  17. Laptev, I. (2006). Improvements of object detection using boosted histograms. In Proceedings of the British Machine Vision Conference.
  18. Lin, Z. and Davis, L. S. (2008). Learning pairwise dissimilarity profiles for appearance recognition in visual surveillance. In ISVC, pages 23-34.
  19. Mikolajczyk, K., Schmid, C., and Zisserman, A. (2004). Human detection based on a probabilistic assembly of robust part detectors. In ECCV.
  20. Mohan, A., Papageorgiou, C., and Poggio, T. (2001). Example-based object detection in images by components. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23:349-361.
  21. Park, U., Jain, A., Kitahara, I., Kogure, K., and Hagita, N. (2006). Vise: Visual search engine using multiple networked cameras. In ICPR, pages 1204-1207.
  22. Prosser, B., Zheng, W.-S., Gong, S., and Xiang, T. (2010). Person re-identification by support vector ranking. In BMVC, pages 21.1-21.11.
  23. Schwartz, W. R. and Davis, L. S. (2009). Learning discriminative appearance-based models using partial least squares. In SIBGRAPI, pages 322-329.
  24. Trefny, J. and Matas, J. (2010). Extended Set of Local Binary Patterns for Rapid Object Detection. In Computer Vision Winter Workshop 2010 - CVWW10.
  25. Tuzel, O., Porikli, F., and Meer, P. (2008). Pedestrian detection via classification on riemannian manifolds. PAMI, 30(10).
  26. Velardo, C. and Dugelay, J. (2010). Face recognition with daisy descriptors. In MM'10 and Sec'10, ACM SIGMM Multimedia and Security Workshop, September 9-10, Rome, Italy.
  27. Viola, P. and Jones, M. (2004). Robust real-time face detection. In International Journal of Computer Vision.
  28. Wang, X., Doretto, G., Sebastian, T., Rittscher, J., and Tu, P. (2007). Shape and appearance context modeling. In ICCV, pages 1-8.
  29. Wang, X., Han, T., and Yan, S. (2009). An hog-lbp human detector with partial occlusion handling. ICCV09 - International Conference on Computer Vision.
  30. Zhu, Q., Avidan, S., Yeh, M., and Cheng, K. (2006). Fast human detection using a cascade of histograms of oriented gradients. In Computer Vision and Pattern Recognition - CVPR.
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Paper Citation


in Harvard Style

Corvee E., Bak S. and Brémond F. (2012). PEOPLE DETECTION AND RE-IDENTIFICATION FOR MULTI SURVEILLANCE CAMERAS . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2012) ISBN 978-989-8565-03-7, pages 82-88. DOI: 10.5220/0003808600820088


in Bibtex Style

@conference{visapp12,
author={Etienne Corvee and Slawomir Bak and François Brémond},
title={PEOPLE DETECTION AND RE-IDENTIFICATION FOR MULTI SURVEILLANCE CAMERAS},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2012)},
year={2012},
pages={82-88},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003808600820088},
isbn={978-989-8565-03-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2012)
TI - PEOPLE DETECTION AND RE-IDENTIFICATION FOR MULTI SURVEILLANCE CAMERAS
SN - 978-989-8565-03-7
AU - Corvee E.
AU - Bak S.
AU - Brémond F.
PY - 2012
SP - 82
EP - 88
DO - 10.5220/0003808600820088