Absbact-In this paper, we investigate data fusion techniques for target tracking using distributed sensors. Specifically, we are interested in how pairs of hearing or range sensors can be best assigned to targets in order to minimize the expected error in the estimates. We refer to this as the focus of attention (FOA) problem. In its general form, FOA is NP-hard and not well approximable. However, for specific geometries we obtain significant approximation results: a 2-approximation algorithm for stem cameras on a line, a PTAS for when the cameras are equidistant, and a 1.42 approximation for equally spaced range sensors on a circle. By reposing as a maximization problem -where the goal is to maximize the number of tracks with bounded error -we are able to leverage results from maximum set-packing to render the problem approximable. We demonstrate the results in simulation for a target tracking task, and for localizing a team of mobile agents in a sensor network. These results prov<de insights into sensodtarget assignment strategies, as well as Sensor placement in a distributed network.
Online camera selection, also referred to as the focus of attention problem by REF , is introduced as a result of the improved mobility of cameras.
Target tracking with distributed sensors: the focus of attention problem
Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453)
Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453)
Computer Science