Authors:
Sebastien Poullot
1
and
Shin'Ichi Satoh
2
Affiliations:
1
NII and JFLI, Japan
;
2
NII and University of Tokyo, Japan
Keyword(s):
Video Segmentation, Points of Interest, Outliers Removal, Frame Alignment, Motion M-layer, GrabCut.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Image and Video Analysis
;
Motion, Tracking and Stereo Vision
;
Optical Flow and Motion Analyses
;
Segmentation and Grouping
Abstract:
This paper introduces VabCut, a video extension of GrabCut, an original unsupervised solution to tackle the video foreground object segmentation task. Vabcut works on an extension of the RGB colour domain to RGBM, where M is the motion. It requires a prior step: the computation of the motion layer (M-layer) of the frame to segment. In order to compute this layer we propose to intersect the frame to segment with N temporally close aligned frames. This paper also introduces a new iterative and collaborative method for an optimal frame alignment, based on points of interest and RANSAC, which automatically discards outliers and refines the homographies in turns. The whole method is fully automatic and can handle standard video, i.e. not professional, shaky, blurry or else. We tested VabCut on the SegTrack 2011 benchmark, and demonstrated
its effectiveness, it especially outperforms the state of the art methods while being faster.