Autonomous Multicamera Tracking on Embedded Smart Cameras
EURASIP Journal on Embedded Systems volume 2007, Article number: 092827 (2007)
There is currently a strong trend towards the deployment of advanced computer vision methods on embedded systems. This deployment is very challenging since embedded platforms often provide limited resources such as computing performance, memory, and power. In this paper we present a multicamera tracking method on distributed, embedded smart cameras. Smart cameras combine video sensing, processing, and communication on a single embedded device which is equipped with a multiprocessor computation and communication infrastructure. Our multicamera tracking approach focuses on a fully decentralized handover procedure between adjacent cameras. The basic idea is to initiate a single tracking instance in the multicamera system for each object of interest. The tracker follows the supervised object over the camera network, migrating to the camera which observes the object. Thus, no central coordination is required resulting in an autonomous and scalable tracking approach. We have fully implemented this novel multicamera tracking approach on our embedded smart cameras. Tracking is achieved by the well-known CamShift algorithm; the handover procedure is realized using a mobile agent system available on the smart camera network. Our approach has been successfully evaluated on tracking persons at our campus.
Wolf W, Ozer B, Lv T: Smart cameras as embedded systems. Computer 2002,35(9):48-53. 10.1109/MC.2002.1033027
Bramberger M, Doblander A, Maier A, Rinner B, Schwabach H: Distributed embedded smart cameras for surveillance applications. Computer 2006,39(2):68-75. 10.1109/MC.2006.55
Rinner B, Wolf W (Eds): Proceedings of the Workshop on Distributed Smart Cameras (DSC '06) , Boulder, Colo, USA; 2006.
Bradski GR: Computer vision face tracking for use in a perceptual user interface. Intel Technology Journal 1998,2(2):15.
Bramberger M, Quaritsch M, Winkler T, Rinner B, Schwabach H: Integrating multi-camera tracking into a dynamic task allocation system for smart cameras. Proceedings of IEEE Conference on Advanced Video and Signal Based Surveillance (AVSS '05), September 2005, Como, Italy 474-479.
Heyrman B, Paindavoine M, Schmit R, Letellier L, Collette T: Smart camera design for intensive embedded computing. Real-Time Imaging 2005,11(4):282-289. 10.1016/j.rti.2005.04.006
Rowe A, Rosenberg C, Nourbakhsh I: A second generation low cost embedded color vision system. Proceedings of IEEE Embedded Computer Vision Workshop (ECVW '05) in conjunction with IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '05), June 2005, San Diego, Calif, USA 3: 136.
Micheloni C, Foresti GL, Snidaro L: A network of co-operative cameras for visual surveillance. IEE Proceedings: Vision, Image and Signal Processing 2005,152(2):205-212. 10.1049/ip-vis:20041256
Fleck S, Straßer W: Adaptive probabilistic tracking embedded in a smart camera. Proceedings of IEEE Embedded Computer Vision Workshop (ECVW '05) in conjunction with IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '05), June 2005, San Diego, Calif, USA 3: 134.
Fleck S, Busch F, Biber P, Straßer W: 3D surveillance—a distributed network of smart cameras for real-time tracking and its visualization in 3D. Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '06), June 2006, New York, NY, USA 118.
Velipasalar S, Schlessman J, Chen C-Y, Wolf W, Singh JP: SCCS: a scalable clustered camera system for multiple object tracking communicating via message passing interface. Proceedings of IEEE International Conference on Multimedia and Expo, July 2006, Toronto, ON, Canada 277-280.
Remagnino P, Orwell J, Greenhill D, Jones GA, Marchesotti L: An agent society for scene interpretation. In Multimedia Video Based Surveillance Systems: Requirements, Issues and Solutions. Kluwer Academic, Boston, Mass, USA; 2001:108-117.
Abreu B, Botelho L, Cavallaro A, et al.: Video-based multi-agent traffic surveillance system. Proceedings of IEEE Intelligent Vehicles Symposium (IV '00), October 2000, Dearbon, Mich, USA 457-462.
Doblander A, Rinner B, Trenkwalder N, Zoufal A: A middleware framework for dynamic reconfiguration and component composition in embedded smart cameras. WSEAS Transactions on Computers 2006,5(3):574-581.
Karnik NM, Tripathi AR: Design issues in mobile agent programming systems. IEEE Concurrency 1998,6(3):52-61. 10.1109/4434.708256
Bramberger M, Rinner B, Schwabach H: A method for dynamic allocation of tasks in clusters of embedded smart cameras. Proceedings of IEEE International Conference on Systems, Man and Cybernetics (SMC '05), October 2005, Waikoloa, Hawaii, USA 3: 2595-2600.
Jurie F, Dhome M: Real time robust template matching. Proceedings of the British Machine Vision Conference (BMVC '02), September 2002, Cardiff, UK 123-132.
Hager GD, Belhumeur PN: Efficient region tracking with parametric models of geometry and illumination. IEEE Transactions on Pattern Analysis and Machine Intelligence 1998,20(10):1025-1039. 10.1109/34.722606
Black MJ, Jepson AD: Eigentracking: robust matching and tracking of articulated objects using a view-based representation. International Journal of Computer Vision 1998,26(1):63-84. 10.1023/A:1007939232436
Koller D, Daniilidis K, Nagel HH: Model-based object tracking in monocular image sequences of road traffic scenes. International Journal of Computer Vision 1993,10(3):257-281. 10.1007/BF01539538
Beleznai C, Frühstück B, Bischof H: Human detection in groups using a fast mean shift procedure. Proceedings of International Conference on Image Processing (ICIP '04), October 2004, Singapore 1: 349-352.
Shi J, Tomasi C: Good features to track. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '94), June 1994, Seattle, Wash, USA 593-600.
Comaniciu D, Ramesh V, Meer P: Real-time tracking of non-rigid objects using mean shift. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '00), June 2000, Hilton Head Island, SC, USA 2: 142-149.
Avidan S: Support vector tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence 2004,26(8):1064-1072. 10.1109/TPAMI.2004.53
Williams O, Blake A, Cipolla R: Sparse Bayesian learning for efficient visual tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence 2005,27(8):1292-1304.
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Quaritsch, M., Kreuzthaler, M., Rinner, B. et al. Autonomous Multicamera Tracking on Embedded Smart Cameras. J Embedded Systems 2007, 092827 (2007). https://doi.org/10.1155/2007/92827