Staff Members - Benha University
A ROBUST APPROACH FOR OBJECT TRACKING BASED ON PARTICLE FILTER AND OPTIMIZED LIKELIHOOD
International Association of Scientific Innovation and Research • 2014
Publication Information
Authors
Amr M Nagy, Ali Ahmed, Hala H Zayed
Keywords
Not Available
Journal
International Association of Scientific Innovation and Research
Publisher
Not Available
Volume
7
Issue
1
Pages
54-61
publication.type
International
Paper Link
Open Link
Supplementary Materials
Not Available
Abstract
Abstract: Robust tracking of non-rigid objects is a challenging task. Particle filter is a
powerful tool for vision tracking based on sequential Monte Carlo framework and proved
very successful for non-linear and non-Gaussian estimation problem. This paper proposes a
tracking algorithm based on particle filter and optimized Likelihood. Colour distributions are
applied as they are robust to partial occlusion, rotation, scale invariant and computationally
efficient. As the colour of an object can vary over time dependent on the illumination, the
powerful tool for vision tracking based on sequential Monte Carlo framework and proved
very successful for non-linear and non-Gaussian estimation problem. This paper proposes a
tracking algorithm based on particle filter and optimized Likelihood. Colour distributions are
applied as they are robust to partial occlusion, rotation, scale invariant and computationally
efficient. As the colour of an object can vary over time dependent on the illumination, the