PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A hierarchical system for recognition, tracking and pose estimation
Philipp Zehnder, Esther Koller-Meier, Rik Fransens, Luc Van Gool and Luc Van Gool
In: Cognitive Vision Systems (2005) Springer , Germany .

Abstract

This chapter presents a system for the recognition, tracking and pose estimation of people in video sequences. It is based on a careful selection of Haar wavelet features and uses Support Vector Machines (SVM) in spaces of reduced dimensionality for classification. Recognition is carried out hierarchically by using a set of detectors and discriminators for people and poses. The characteristic fea- tures used in the individual nodes are learned automatically. Tracking is solved via a particle filter that utilizes the SVM output and a first order kinematic model to obtain a robust scheme that successfully handles occlusion, different poses and camera zooms.

EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:1580
Deposited By:Rik Fransens
Deposited On:28 November 2005