Journal
IMAGE AND VISION COMPUTING
Volume 21, Issue 1, Pages 99-110Publisher
ELSEVIER
DOI: 10.1016/S0262-8856(02)00129-4
Keywords
particle filtering; condensation algorithm; color distribution; bhattacharyya coefficient; mean shift tracker
Ask authors/readers for more resources
Robust real-time tracking of non-rigid objects is a challenging task. Particle filtering has proven very successful for non-linear and non-Gaussian estimation problems. The article presents the integration of color distributions into particle filtering, which has typically been used in combination with edge-based image features. Color distributions are applied, as they are robust to partial occlusion, are rotation and scale invariant and computationally efficient. As the color of an object can vary over time dependent on the illumination, the visual angle and the camera parameters, the target model is adapted during temporally stable image observations. An initialization based on an appearance condition is introduced since tracked objects may disappear and reappear. Comparisons with the mean shift tracker and a combination between the mean shift tracker and Kalman filtering show the advantages and limitations of the new approach. (C) 2002 Elsevier Science B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available