By Topic

A New Approach to the Use of Edge Extremities for Model-based 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

4 Author(s)
Youngrock Yoon ; Robot Vision Lab Purdue University West Lafayette, IN 47907 U.S.A. yoony@ecn.purdue.edu ; Kosaka, A. ; Jae Byung Park ; Kak, A.C.

This paper presents a robust model-based visual tracking algorithm that can give accurate 3D pose of a rigid object. Our tracking algorithm uses an incremental pose update scheme in a prediction-verification framework. Extended Kalman filter is used to update the pose of a target incrementally to minimize the error between the expected map of the target model and the corresponding gradient edge in the image space. The main contributions of this paper include: 1) A novel approach to how we use the two extremities of straight-lines as features. By taking into account the measurement uncertainties associated with the locations of the extracted extremities of the straight-line, our approach can compare correctly two straight-lines of different lengths. 2) Our use of a test of mean criterion for initiating backtracking and our use of a variable threshold on the output of this criterion that makes nil-matching more effective. We have tested our tracking algorithm with image sequences containing highly cluttered backgrounds. The system successfully tracks objects even when they are highly occluded.

Published in:

Robotics and Automation, 2005. ICRA 2005. Proceedings of the 2005 IEEE International Conference on

Date of Conference:

18-22 April 2005