Title :
Hierarchically-constrained optical flow
Author :
Ryan Kennedy;Camillo J. Taylor
Author_Institution :
Department of Computer and Information Science, University of Pennsylvania, USA
fDate :
6/1/2015 12:00:00 AM
Abstract :
This paper presents a novel approach to solving optical flow problems using a discrete, tree-structured MRF derived from a hierarchical segmentation of the image. Our method can be used to find globally-optimal matching solutions even for problems involving very large motions. Experiments demonstrate that our approach is competitive on the MPI-Sintel dataset and that it can significantly outperform existing methods on problems involving large motions.
Keywords :
"Cost function","Optical imaging","Image segmentation","Computational modeling","Motion segmentation","Image edge detection"
Conference_Titel :
Computer Vision and Pattern Recognition (CVPR), 2015 IEEE Conference on
Electronic_ISBN :
1063-6919
DOI :
10.1109/CVPR.2015.7298955
