By Topic

Minimum-error active matching for real-time vision

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
$33 $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)
Zhibin Liu ; Tsinghua National Laboratory for Information, Science and Technology, Department of Automation, Tsinghua University, Beijing, 100084, China ; Zongying Shi ; Wenli Xu

As an integral part of real-time vision system, there are two most important requirements for feature matching mechanisms: high computational efficiency for meeting the real-time demands, and high correct matching rate for ensuring the convergence and consistency of state estimation. Both of these are addressed and solved as an integrated whole by the efficient minimum-error active matching scheme proposed in this paper. Image processing is performed in a dynamically guided fashion by checking only parts of the image where positive matches are most probable. For achieving the global consensus matchings, rigorous analysis on how to minimize the matching errors in active matching by choosing an optimal search order is made. After that, practical feature matching algorithms are given, which have naturally absorbed the ideas of nearest neighbor (NN) and joint compatibility branch and bound (JCBB) approaches. Both statistical simulations and real-world experimental results have verified the proposed methods can perform better than the state-of-the-art algorithms, i.e. being able to obtain the best global consensus matchings with much lower computational cost.

Published in:

Robotics and Automation (ICRA), 2010 IEEE International Conference on

Date of Conference:

3-7 May 2010