A tracker for multiple dynamic targets using multiple sensors

Summer Adams
Maria Hybinette
Tucker Balch
IEEE International Conference on Robotics and Automation (2007), pp. 3140-3141

Abstract

We describe a clustering-based algorithm for tracking a dynamically varying number of targets observed by multiple sensors. The algorithm relies on discrete target detections (e.g., laser "hits") and a simple model of the targets to be tracked (e.g. a human is modeled in 2-D as a circle). The algorithm is evaluated in the context of a 4 versus 4 basketball game (8 targets) using 4 SICK LMS291 laser scanners as input. Our evaluations show that the sensor system correctly reports the number of targets roughly 99% of the time. We also demonstrate use of the tracker with two video datasets of multiple changing numbers of ants and fish, respectively.