TY  - CONF
AU  - Jose Carlos Rubio
AU  - Joan Serrat
AU  - Antonio Lopez
A2  - ACCV
PY  - 2012//
TI  - Video Co-segmentation
T2  - LNCS
BT  - 11th Asian Conference on Computer Vision
SP  - 13
EP  - 24
VL  - 7725
PB  - Springer Berlin Heidelberg
N2  - Segmentation of a single image is in general a highly underconstrained problem. A frequent approach to solve it is to somehow provide prior knowledge or constraints on how the objects of interest look like (in terms of their shape, size, color, location or structure). Image co-segmentation trades the need for such knowledge for something much easier to obtain, namely, additional images showing the object from other viewpoints. Now the segmentation problem is posed as one of differentiating the similar object regions in all the images from the more varying background. In this paper, for the first time, we extend this approach to video segmentation: given two or more video sequences showing the same object (or objects belonging to the same class) moving in a similar manner, we aim to outline its region in all the frames. In addition, the method works in an unsupervised manner, by learning to segment at testing time. We compare favorably with two state-of-the-art methods on video segmentation and report results on benchmark videos.
SN  - 0302-9743
SN  - 978-3-642-37443-2
L1  - http://refbase.cvc.uab.es/files/RSL2012d.pdf
UR  - http://dx.doi.org/10.1007/978-3-642-37444-9_2
N1  - ADAS
ID  - Jose Carlos Rubio2012
ER  -