Object tracking in the presence of occlusions via a camera network.
01/2007; pp.509-518 In proceeding of: Proceedings of the 6th International Conference on Information Processing in Sensor Networks, IPSN 2007, Cambridge, Massachusetts, USA, April 25-27, 2007
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ABSTRACT: System design aspects must be considered to effectively map an application onto the constraints of a smart cam-era network. Therefore, we propose an application-driven design methodology that enables the determination of an output set of operation parameters given an input set of application requirements. We illustrate this approach utilizing distributed, sequential Bayesian estimation for several applications including target tracking, occupancy sensing and multi-object tracking. Observation models for single camera and stereo vision systems are introduced with a particular focus on low-resolution image sensors. Early simulation results indi-cate that (i) stereo vision can increase tracking accuracy by about a factor of five over single camera vision and (ii) doubling camera resolution can result in more than twice the accuracy. Introduction Information-intensive smart camera networks have re-cently received much attention [1, 2] partly due to their potential ability of simplifying and enhancing existing applications or even of enabling previously infeasible applications. Promising applications include intelligent surveillance, smart homes, ambient intelligence, and el-derly care.
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