Scheduled System Maintenance on May 29th, 2015:
IEEE Xplore will be upgraded between 11:00 AM and 10:00 PM EDT. During this time there may be intermittent impact on performance. We apologize for any inconvenience.
By Topic

Image flow segmentation and estimation by constraint line clustering

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

1 Author(s)
Schunck, B.G. ; Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA

Image flow is the velocity field in the image plane caused by the motion of the observer, objects in the scene, or apparent motion, and can contain discontinuities due to object occlusion in the scene. An algorithm that can estimate the image flow velocity field when there are discontinuities due to occlusions is described. The constraint line clustering algorithm uses a statistical test to estimate the image flow velocity field in the presence of step discontinuities in the image irradiance or velocity field. Particular emphasis is placed on motion estimation and segmentation in situations such as random dot patterns where motion is the only cue to segmentation. Experimental results on a demanding synthetic test case and a real image are presented. A smoothing algorithm for improving the velocity field estimate is also described. The smoothing algorithm constructs a smooth estimate of the velocity field by approximating a surface between step discontinuities. It is noted that the velocity field estimate can be improved using surface reconstruction between velocity field boundaries

Published in:

Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:11 ,  Issue: 10 )