Real-time Target Tracking Using a Pan and Tilt Platform

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.





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/