DocumentCode
791924
Title
Accurate dense optical flow estimation using adaptive structure tensors and a parametric model
Author
Liu, Haiying ; Chellappa, Rama ; Rosenfeld, Azriel
Author_Institution
Center for Autom. Res., Univ. of Maryland, College Park, MD, USA
Volume
12
Issue
10
fYear
2003
Firstpage
1170
Lastpage
1180
Abstract
An accurate optical flow estimation algorithm is proposed in this paper. By combining the three-dimensional (3D) structure tensor with a parametric flow model, the optical flow estimation problem is converted to a generalized eigenvalue problem. The optical flow can be accurately estimated from the generalized eigenvectors. The confidence measure derived from the generalized eigenvalues is used to adaptively adjust the coherent motion region to further improve the accuracy. Experiments using both synthetic sequences with ground truth and real sequences illustrate our method. Comparisons with classical and recently published methods are also given to demonstrate the accuracy of our algorithm.
Keywords
adaptive estimation; eigenvalues and eigenfunctions; image sequences; parameter estimation; tensors; 3D structure tensor; accuracy; adaptive structure tensors; coherent motion region; confidence measure; dense optical flow estimation; generalized eigenvalue problem; generalized eigenvectors; ground truth; parametric flow model; parametric model; real sequences; synthetic sequences; three-dimensional structure tensor; Adaptive optics; Biomedical optical imaging; Eigenvalues and eigenfunctions; Image motion analysis; Motion analysis; Motion estimation; Nonlinear optics; Optical sensors; Parametric statistics; Tensile stress;
fLanguage
English
Journal_Title
Image Processing, IEEE Transactions on
Publisher
ieee
ISSN
1057-7149
Type
jour
DOI
10.1109/TIP.2003.815296
Filename
1233560
Link To Document