Summary
International Symposium on Nonlinear Theory and its Applications
2010
Session Number:A2L-B
Session:
Number:A2L-B2
Hierarchical Feature Extraction for Dynamic Feature and Signature Tracking
Vilmos Szabo, Csaba Rekeczky,
pp.95-98
Publication Date:2010/9/5
Online ISSN:2188-5079
Summary:
The goal of this paper is to introduce an improved tracking framework, which exploits dynamic feature and signature selection techniques for data association models. It performs robust multiple object tracking in a noisy, cluttered environment with closely spaced targets. This method extends the back-end processing capabilities of tracking systems by creating a two-level hierarchy between the parallelly extracted features. These features are dynamically selected based on a spatio-temporal consistency weight function, which maximizes the robustness of data association, and reduces the overall complexity of the algorithm.