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

Author

Schleicher, David ; Bergasa, Luis M. ; Barea, Rafael ; López, Elena

Author_Institution

Airbus - Spain, Madrid

Volume

2

fYear

2005

fDate

21-24 Nov. 2005

Firstpage

999

Lastpage

1002

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

Keywords

computer vision; object detection; object recognition; particle filtering (numerical methods); principal component analysis; target tracking; 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; Head; Humans; Linear discriminant analysis; Object detection; Particle filters; Particle tracking; Principal component analysis; State estimation; Support vector machine classification; Support vector machines; People detection; components particle filter; multiple object tracking; people tracking;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer as a Tool, 2005. EUROCON 2005.The International Conference on

Conference_Location

Belgrade

Print_ISBN

1-4244-0049-X

Type

conf

DOI

10.1109/EURCON.2005.1630116

Filename

1630116