Dynamic Sensor Selection for Single Target Tracking in Large Video Surveillance Networks

Abstract

In this paper an approach for dynamic camera selectionin large video-based sensor networks for the purposeof multi-camera object tracking is presented. The sensor selectionapproach is based on computational geometry algorithmsand is able to determine task-relevant cameras (cameracluster) by evaluation of geometrical attributes, giventhe last observed object position, the sensor configurationsand a building map. A special goal of this algorithm is theefficient determination of the minimum number of sensorsneeded to relocate an object, even if the object is temporarilyout of sight. In particular, the approach is applicablein camera networks with overlapping and non-overlappingfield of views as well as with static and non-static sensors.