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A tracking algorithm for PTZ cameras


D. M. Raimondo, Simone Gasparella, D. Sturzenegger, J. Lygeros, M. Morari

2nd IFAC Workshop on Distributed Estimation and Control in Networked Systems (NecSys'10)

This paper presents a tracking algorithm for PTZ (pan-tilt-zoom) cameras. The tracked objects are Mini 1:43 scale RC cars that have been described by an unicycle model. The algorithm is based on the combination of EKF (Extended Kalman Filter) and Particle Filters. A scanning procedure is used in order to explore the environment. Once the target is detected, EKF is used in order to predict its future position. Then, the PTZ camera is moved in order to center the target predicted position. Since the camera view is limited, it is possible to lose the target. When target is lost, particle filter is exploited. PTZ is then moved in order to maximize the future probability of detection. If the target is not found in few steps, then particle filter is stopped and a scanning procedure restarts.


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% Autogenerated BibTeX entry
@InProceedings { RaiEtal:2010:IFA_3598,
    author={D. M. Raimondo and Simone Gasparella and D. Sturzenegger and J.
	  Lygeros and M. Morari},
    title={{A tracking algorithm for PTZ cameras}},
    booktitle={2nd IFAC Workshop on Distributed Estimation and Control in
	  Networked Systems (NecSys'10)},
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