Please use this identifier to cite or link to this item:
|Scopus||Web of Science®||Altmetric|
|Title:||Locally oriented optical flow computation|
|Citation:||IEEE Transactions on Image Processing, 2012; 21(4):1573-1586|
|Publisher:||IEEE-Inst Electrical Electronics Engineers Inc|
|Yan Niu, Anthony Dick and Michael Brooks|
|Abstract:||This paper proposes the use of an adaptive locally oriented coordinate frame when calculating an optical flow field. The coordinate frame is aligned with the least curvature direction in a local window about each pixel. This has advantages to both fitting the flow field to the image data and in imposing smoothness constraints between neighboring pixels. In terms of fitting, robustness is obtained to a wider variety of image motions due to the extra invariance provided by the coordinate frame. Smoothness constraints are naturally propagated along image boundaries which often correspond to motion boundaries. In addition, moving objects can be efficiently segmented in the least curvature direction. We show experimentally the benefits of the method and demonstrate robustness to fast rotational motion, such as what often occurs in human motion.|
|Keywords:||Directional derivative; image structure; intrinsicdirection detection; motion estimation; optical flow|
|Rights:||© 2011 IEEE|
|Appears in Collections:||Computer Science publications|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.