ECCV
2008
Springer
14 years 6 months ago
2008
Springer
Abstract. Variational problems, which are commonly used to solve lowlevel vision tasks, are typically minimized via a local, iterative optimization strategy, e.g. gradient descent....
ECCV
2008
Springer
14 years 6 months ago
2008
Springer
Assumptions of brightness constancy and spatial smoothness underlie most optical flow estimation methods. In contrast to standard heuristic formulations, we learn a statistical mod...
ECCV
2008
Springer
14 years 6 months ago
2008
Springer
Segmentation has gained in popularity in stereo matching. However, it is not trivial to incorporate it in optical flow estimation due to the possible non-rigid motion problem. In t...
ICCV
2007
IEEE
14 years 6 months ago
2007
IEEE
This paper presents a method for scene flow estimation from a calibrated stereo image sequence. The scene flow contains the 3-D displacement field of scene points, so that the 2-D...
CVPR
2008
IEEE
14 years 6 months ago
2008
IEEE
Accurate estimation of optical flow is a challenging task, which often requires addressing difficult energy optimization problems. To solve them, most top-performing methods rely ...
CVPR
2008
IEEE
14 years 6 months ago
2008
IEEE
Optical flow estimation requires spatial integration, which essentially poses a grouping question: what points belong to the same motion and what do not. Classical local approache...
CVPR
1997
IEEE
14 years 6 months ago
1997
IEEE
A framework for learning parameterized models of optical flow from image sequences is presented. A class of motions is represented by a set of orthogonal basis flow fields that ar...