Authors:
Roberto P. Palomares
;
Gloria Haro
and
Coloma Ballester
Affiliation:
Universitat Pompeu Fabra, Spain
Keyword(s):
Scene Flow, Variational Methods, Coordinate Descent, Sparse Matches.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Geometry and Modeling
;
Image-Based Modeling
;
Motion, Tracking and Stereo Vision
;
Optical Flow and Motion Analyses
;
Pattern Recognition
;
Software Engineering
Abstract:
This paper presents a novel variational approach for the joint estimation of scene flow and occlusions. Our method does not assume that a depth sensor is available. Instead, we use a stereo sequence and exploit the fact that points that are occluded in time, might be visible from the other view and thus the 3D geometry can be densely reinforced in an appropriate manner through a simultaneous motion occlusion characterization. Moreover, large displacements are correctly captured thanks to an optimization strategy that uses a set of sparse image correspondences to guide the minimization process. We include qualitative and quantitative experimental results on several datasets illustrating that both proposals help to improve the baseline results.