PhD Thesis

People Tracking and Recognition using the Multi-Object Particle Filter Algorithm and Hierarchical PCA Method

Schleicher, David; Bergasa, Luis M.; Barea, Rafael; López, Elena
Year: 2005
Type of Publication: In Proceedings
Keywords: body parts; component particle filter; geometrical constraints; hierarchical principal component analysis; moving object; multiobject particle filter algorithm; multiple object tracking; people detection; people recognition; people tracking; computer vision; object
Volume: 2
Book title: Computer as a Tool, 2005. EUROCON 2005.The International Conference on
Pages: 999 -1002
Month: nov.
DOI: 10.1109/EURCON.2005.1630116
Abstract:
This paper presents a method to detect, recognize and track people using mount cameras fixed on a building. The method consists of two independent stages. One is dedicated to detect and track any moving object within the image frame. The other one is in charge to discard any moving object that is not a human being. To perform the first task, a particle filter algorithm is used, in such way that it can perform the tracking of multiple objects. For the recognition stage a PCA (principal components analysis) method is applied to several body parts (head, arms, etc.) respecting their geometrical constraints. The performance of the system has been tested successfully. Some experimental results and conclusions are presented
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