By Topic

A new combination of local and global constraints for optical flow computation

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)
Y. Niu ; School of Computer Science, University of Adelaide, Australia ; A. Dick ; M. Brooks

This paper describes an approach to optical flow computation that combines local and global constraints. A local flow estimate is obtained at each pixel, and is used to segment the image into regions of smooth motion. Within each region, global constraints are applied to reduce noise in local flow estimates while preserving motion boundaries. The main novel contributions in this framework are: (1) the derivation of a consistency measure for local flow computation, and the use of this measure to preserve motion boundary in the estimation; (2) the combined use of global subspace and spatial smoothness constraints to complement local flow estimation. Results on standard test sequences demonstrate improved accuracy in flow estimation, and analyse the role that each contribution plays in this improvement.

Published in:

2008 23rd International Conference Image and Vision Computing New Zealand

Date of Conference:

26-28 Nov. 2008