Cooperative Object Tracking with Multiple PTZ Cameras

Research in visual surveillance systems is shifting from using few stationary, passive cameras to employing large heterogeneous sensor networks. One promising type of sensor in particular is the pan-tilt-zoom (PTZ) camera, which can cover a potentially much larger area than passive cameras, and can obtain much higher resolution imagery through zoom capacity. In this paper, a system that can track objects with multiple calibrated PTZ cameras in a cooperative fashion is presented. Tracking and calibration results are combined with several image processing techniques in a statistical segmentation framework, through which the cameras can hand over targets to each other. A prototype system is presented that operates in real time.

[1]  Brett Browning,et al.  Person tracking from a dynamic balancing platform , 2004 .

[2]  T. Kanade,et al.  A master-slave system to acquire biometric imagery of humans at distance , 2003, IWVS '03.

[3]  Carlo S. Regazzoni,et al.  Cooperative multisensor system for real-time face detection and tracking in uncontrolled conditions , 2005, IS&T/SPIE Electronic Imaging.

[4]  Max Lu,et al.  Acquiring Multi-Scale Images by Pan-Tilt-Zoom Control and Automatic Multi-Camera Calibration , 2005, 2005 Seventh IEEE Workshops on Applications of Computer Vision (WACV/MOTION'05) - Volume 1.

[5]  Ben J. A. Kröse,et al.  Online multicamera tracking with a switching state-space model , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[6]  R. Bowden,et al.  Towards automated wide area visual surveillance: tracking objects between spatially-separated, uncalibrated views , 2005 .

[7]  Tim J. Ellis,et al.  Multi camera image tracking , 2006, Image Vis. Comput..

[8]  Dorin Comaniciu,et al.  Kernel-Based Object Tracking , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Christian Schlegel,et al.  Integrating Vision Based Behaviours with an Autonomous Robot , 1999, ICVS.

[10]  Paolo Remagnino,et al.  Distributed intelligence for multi-camera visual surveillance , 2004, Pattern Recognit..

[11]  Takeo Kanade,et al.  Algorithms for cooperative multisensor surveillance , 2001, Proc. IEEE.

[12]  Ben J. A. Kröse,et al.  Keeping Track of Humans: Have I Seen This Person Before? , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[13]  Dorin Comaniciu,et al.  Mean Shift: A Robust Approach Toward Feature Space Analysis , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  Dorin Comaniciu,et al.  Real-time tracking of non-rigid objects using mean shift , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[15]  Ben J. A. Kröse,et al.  A sequential Bayesian algorithm for surveillance with nonoverlapping cameras , 2005, Int. J. Pattern Recognit. Artif. Intell..

[16]  Larry D. Hostetler,et al.  The estimation of the gradient of a density function, with applications in pattern recognition , 1975, IEEE Trans. Inf. Theory.

[17]  James Orwell,et al.  Learning the Semantic Landscape: embedding scene knowledge in object tracking , 2005, Real Time Imaging.

[18]  M.D. Naish,et al.  Active-vision-based multisensor surveillance - an implementation , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).