By Topic

Histogram correlation based classifier fusion for object tracking

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

2 Author(s)
Topkaya, I.S. ; Sabanci Univ., Istanbul, Turkey ; Erdogan, H.

Mean shift is a popular method used in object tracking. The method, which relies on shifting the search area to the weight center of a generated “weight image” to track objects between consecutive frames, acquired a classifier based framework by using classifiers to generate the weight image. In this work, using multiple classifiers to generate the weight image and calculating contributions of the independent classifiers dynamically by using correlations between histograms of their weight images and histogram of a defined ideal weight image are presented.

Published in:

Signal Processing and Communications Applications (SIU), 2011 IEEE 19th Conference on

Date of Conference:

20-22 April 2011