Application-Oriented Design of Smart Camera Networks

System design aspects must be considered to effectively map an application onto the constraints of a smart camera 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 indicate 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.