Real-time Target Tracking Using a Pan and Tilt Platform

Authors: Moulay A. Akhloufi

Abstract:

In recent years, we see an increase of interest for efficient tracking systems in surveillance applications. Many of the proposed techniques are designed for static cameras environments. When the camera is moving, tracking moving objects become more difficult and many techniques fail to detect and track the desired targets. The problem becomes more complex when we want to track a specific object in real-time using a moving Pan and Tilt camera system to keep the target within the image. This type of tracking is of high importance in surveillance applications. When a target is detected at a certain zone, the possibility of automatically tracking it continuously and keeping it within the image until action is taken is very important for security personnel working in very sensitive sites. This work presents a real-time tracking system permitting the detection and continuous tracking of targets using a Pan and Tilt camera platform. A novel and efficient approach for dealing with occlusions is presented. Also a new intelligent forget factor is introduced in order to take into account target shape variations and avoid learning non desired objects. Tests conducted in outdoor operational scenarios show the efficiency and robustness of the proposed approach.

Keywords: Tracking, surveillance, target detection, Pan and tilt.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1060437

References:

[1] Yilmaz, A., Javed, O., and Shah, M., "Object Tracking: A Survey," ACM Journal of Computing Surveys, 38 (4), 1-45 (2006).
[2] Shah, M., Hakeem, A., and Basharat, A., "Detection and Tracking of Objects from Multiple Airborne Cameras," SPIE Newsroom, (2006).
[3] Kang, J., Cohen, I., Medioni, G., and Yuan., C., "Detection and Tracking of Moving Objects from a Moving Platform in Presence of Strong Parallax," Proc. IEEE Int. Conf. on Comp. Vision, (2005).
[4] Yu, Q., Cohen, I., Medioni, G., Wu, B., "Boosted Markov Chain Monte Carlo Data Association for Multiple Targets Detection and Tracking," Proc. Int. Conf. on Patt. Recog., (2006).
[5] Cohen, I. and Medioni, G., "Detecting and Tracking of Objects in Airborne Video Imagery," Proc of IEEE Compt. Vision and Patt. Recog. Interpretation of Visual Motion Workshop, (1998).
[6] Davies, D., Palmer, P. and Mirmehdi, M., "Detection and Tracking of Very Small Low Contrast Objects," Proc. British Machine Vision Conference, 599-608 (1998).
[7] Akhloufi, M., "Tracking multiple-sized objects in low resolution and noisy images," Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications VI. Proceedings of the SPIE, Volume 7307, pp. 73070J-73070J-12 (2009).
[8] Shah, H., and Morrell, D., "An adaptive zoom algorithm for tracking targets using pan-tilt-zoom cameras," Proceedings of the 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, Montreal, Canada (2004).
[9] Cindy, X. Collange, F. Jurie, F. Martinet, P. "Object tracking with a pan-tilt-zoom camera: application to car driving assistance", Proceedings of IEEE International Conference on Robotics and Automation. pp. 1653- 1658 vol.2, Seoul, Korea (2001)
[10] Cuevas, E., Zaldivar, D., and Rojas, R., "Kalman filter for vision tracking," Freie Universität Berlin Institut für Informatik Technical Report B 05-12, (2005).
[11] Cuevas, E., Zaldivar, D., and Rojas, R., "Particle filter in vision tracking," Freie Universität Berlin Institut für Informatik Technical Report B 05-13, (2005).
[12] Directed Perception PTU, http://www.dperception.com/