People Counting in Transport Vehicles
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32804
People Counting in Transport Vehicles

Authors: Sebastien Harasse, Laurent Bonnaud, Michel Desvignes

Abstract:

Counting people from a video stream in a noisy environment is a challenging task. This project aims at developing a counting system for transport vehicles, integrated in a video surveillance product. This article presents a method for the detection and tracking of multiple faces in a video by using a model of first and second order local moments. An iterative process is used to estimate the position and shape of multiple faces in images, and to track them. the trajectories are then processed to count people entering and leaving the vehicle.

Keywords: face detection, tracking, counting, local statistics

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1075844

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1713

References:


[1] S. Ioffe, D. A. Forsyth, "Probabilistic Methods for Finding People". International Journal of Computer Vision 43(1), pp 45-68, 2001.
[2] M.H. Yang, D. Kriegman, and N. Ahuja. "Detecting face in images: a survey", IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(1), pp 34-58, 2002.
[3] Erik Hjelmas "Face Detection: A Survey", Computer Vision and Image Understanding, 83(3), pp. 236-274, 2001.
[4] C. Wren, A. Azarbayejani, T. Darell, A. Pentland, "Pfinder: Real-time tracking of human body", IEEE Trans. on Pattern Analysis and Machine Intelligence, 19(7), pp. 780-785, 1997.
[5] I. Haritaoglu, D. Harwood, and L. Davis, "W4: A real-time system for detection and tracking of people and monitoring their activities", IEEE Pattern Analysis and Machine Intelligence, 22(8), pp. 809-830, 2000.
[6] Collins, Lipton, Kanade, Fujiyoshi, Duggins, Tsin, Tolliver, Enomoto, and Hasegawa, "A System for Video Surveillance and Monitoring: VSAM Final Report," Technical report CMU-RI-TR-00-12, Robotics Institute, Carnegie Mellon University, May, 2000.
[7] G. Yang, T.S. Huang, "Human face detection in complex background", Pattern recognition,27(1):53, 1994.
[8] Y.H. Kwon and N. da Vitoria Lobo, "Face Detection Using Templates", International Conference on Pattern Recognition, pp. 764-767, 1994.
[9] H. Nanda and L. Davis, "Probabilistic template based pedestrian detection in infrared videos". IEEE Intelligent Vehicles, 2002, Versailles, France, pp 15-20, 2002,
[10] M. Bertozzi et al, "Pedestrian detection in infrared images," IEEE Intelligent Vehicles Symposium 2003, Columbus, USA, pp662-667, 2003
[11] C. Stauffer and E. Grimson, "Similarity templates for detection and recognition", Computer Vision and Pattern Recognition, pp. 221-228, Kauai, HI,. 2001.
[12] P. Campadelli, R. Lanzarotti, G. Lipori, "Face detection in color images of generic scenes", International Conference on Computational Intelligence for Homeland Security and Personal Safety (CIHSPS), 2004.
[13] F. Xu, X. Liu, and K. Fujimura, "Pedestrian Detection and Tracking with Night Vision", IEEE Transactions on Intelligent Transportation Systems, 5(4), 2004
[14] L. Zhao and C. Thorpe, "Stereo- and neural network based pedestrian detection", IEEE Int. Conf. on Intelligent Transportation Systems, Tokyo, Japan, pp 148-154, 2000.
[15] H. Rowley, S. Baluja, T. Kanade, "Neural Network-Based Face Detection," IEEE Trans. Pattern Analysis and Machine Intelligence,20(1), pp.23-38, 1998.
[16] M. Isard and A. Blake, "Condensation - conditional density propagation for visual tracking", International Journal of Computer Vision 29(1), pp. 5-28, 1998.
[17] K. Schwerdt and J. L. Crowley, "Robust face tracking using color", in Proc. of 4th International Conference on Automatic Face and Gesture Recognition, Grenoble, France, 2000, pp. 90-95.
[18] M-K. Hu, "Visual pattern recognition by moment invariants", IRE Trans. on Information Theory, IT-8:pp. 179-187, 1962.
[19] P. J. Phillips, H. Moon, P. J. Rauss, and S. Rizvi, "The FERET evaluation methodology for face recognition algorithms", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 22, No. 10, October 2000.