Non-overlapping Distributed Tracking System Utilizing Particle Filter
|dc.contributor.author||Lim, Fee Lee|
|dc.identifier.citation||Lim, Fee Lee and Leoputra, Wilson and Tan, Tele. 2007. Non-overlapping distributed tracking system utilizing particle filter. The Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology. 49 (3): pp. 343-362.|
Tracking people across multiple cameras is a challenging research area in visual computing, especially when these cameras have non-overlapping field of views. The important task is to associate a current subject with other prior appearances of the same subject across time and space in a camera network. Several known techniques rely on Bayesian approaches to perform the matching task. However, these approaches do not scale well when the dimension of the problem increases; e.g. when the number of subject or possible path increases. The aim of this paper is to propose a unified tracking framework using particle filters to efficiently switch between visual tracking (field of view tracking) and track prediction (non-overlapping region tracking). The particle filter tracking system utilizes a map (known environment) to assist the tracking process when targets leave the field of view of any camera. We implemented and tested this tracking approach in an in-house multiple cameras system as well as using on-line data. Promising results were obtained which suggested the feasibility of such an approach.
|dc.title||Non-overlapping Distributed Tracking System Utilizing Particle Filter|
|dcterms.source.title||The Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology|
|curtin.department||Department of Computing|