By Topic

Accurate optical flow estimation using adaptive scale-space and 3D structure tensor

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)
Hai-Yun Wang ; Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore ; Kai-Kuang Ma

Computing optical flow for image sequences is often an essential step to many image processing and computer vision applications. In this paper, a novel, unified optical flow estimation method is developed for simultaneously tackling the aperture problem and multiple motions, and consequently, yielding more accurate optical flow estimation. By integrating Gaussian scale-space with 3D structure tensor, the estimation difficulty encountered in multiple motions resulting from multiple video objects has been handled reasonably well. The obtained normal flow is then treated separately from the real flow, by further applying the least-squares estimation, with the assist of the automatic scale selection mechanism, to produce the estimated real flow. Our proposed automatic scale selection for spatial scale-space is developed from the viewpoint of numerical stability, and the condition number is exploited for adaptively choosing local scales (window sizes). For performance evaluation, we adopted the angular error as the quantitative measurement and used several benchmark image sequences. Experimental results show that the accuracy of our optical flow estimation method is superior to several leading algorithms.

Published in:

Image Processing. 2002. Proceedings. 2002 International Conference on  (Volume:2 )

Date of Conference: