By Topic

A knowledge-based objects tracking algorithm in color video using Kalman filter approach

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)
Mazinan, A.H. ; Electr. Eng. Dept., Islamic Azad Univ. (IAU), Tehran, Iran ; Amir-Latifi, A. ; Kazemi, M.F.

A new knowledge-based algorithm for the purpose of rigid and non-rigid objects tracking through color feature in video sequences is proposed in this research. The mean shift (MS) algorithm, as the efficient method in the area of color-based objects tracking, is improved to solve the tracking problems, such as background with similar colors, partial or full occlusion, sensibly, and so on. In the algorithm presented here, an improved convex kernel function is realized to present a particular solution, since a robust estimator, i.e., Kalman filter approach is correspondingly realized. Experimental results verify that the proposed algorithm is efficient, under sever conditions, while the speed of the object could be constant.

Published in:

Information Retrieval & Knowledge Management (CAMP), 2012 International Conference on

Date of Conference:

13-15 March 2012