Evaluation of the GM-PHD filter for multi-target tracking with a stereo vision system

Document type: Conference Papers
Peer reviewed: Yes
Author(s): Jiandan Chen, Soheil Ghadami, Wlodek Kulesza
Title: Evaluation of the GM-PHD filter for multi-target tracking with a stereo vision system
Conference name: IEEE International Instrumentation and Measurement Technology Conference, I2MTC
Year: 2011
Pagination: 1581-1586
ISBN: 978-142447935-1
Publisher: IEEE
City: Binjiang, Hangzhou
URI/DOI: 10.1109/IMTC.2011.5944129
ISI number: 000297171900318
Organization: Blekinge Institute of Technology
Department: School of Engineering - Dept. of Electrical Engineering (Sektionen för ingenjörsvetenskap - Avd. för elektroteknik)
School of Engineering S-371 79 Karlskrona
+46 455 38 50 00
Language: English
Abstract: This paper evaluates the performance of the Gaussian Mixture Probability Hypothesis Density (GM-PHD) filter for tracking multiple targets in an intelligent vision system. A stereo vision camera is used to get the left and right image sequences in order to extract 3-D coordinates of the targets' positions in the real world scene. The 3-D trajectories of the targets are tracked by a GM-PHD filter. Moreover, the label continuity of the targets is guaranteed by a new method of labeling. Motion speed and angular velocity are proposed for the evaluation of the accuracy and label continuity of the filter in the implemented 3-D test motion model. The simulation results for two moving targets show that the proposed system not only robustly tracks them, but also maintains the label continuity of the two targets.
Subject: Spatial Planning\General
Keywords: Performance Evaluation, Probability Hypothesis Density, Stereo Vision, Trajectory Tracking