By Topic

Robust object tracking using the particle filtering and level set methods: A comparative experiment

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Cheng Luo ; Sch. of Comput. Sci. & Eng., Univ. of New South Wales, Sydney, NSW ; Xiongcai Cai ; Zhang, Jian

Robust visual tracking has become an important topic of research in computer vision. A novel method for robust object tracking, GATE [11], improves object tracking in complex environments using the particle filtering and the level set-based active contour method. GATE creates a spatial prior in the state space using shape information of the tracked object to filter particles in the state space in order to reshape and refine the posterior distribution of the particle filtering. This paper describes a comparative experiment that applies GATE and the standard particle filtering to track the object of interest in complex environments using simple features. Image sequences captured by the hand held, stationary and the PTZ camera are utilised. The experimental results demonstrate that GATE is able to solve the ambiguous outlier problem of particle filters in order to deal with heavy clutters in the background, occlusion, low resolution and noisy images, and thus significantly improves the particle filtering in object tracking.

Published in:

Multimedia Signal Processing, 2008 IEEE 10th Workshop on

Date of Conference:

8-10 Oct. 2008