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Author (up) Jose Carlos Rubio; Joan Serrat; Antonio Lopez edit   pdf
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  Title Video Co-segmentation Type Conference Article
  Year 2012 Publication 11th Asian Conference on Computer Vision Abbreviated Journal  
  Volume 7725 Issue Pages 13-24  
  Keywords  
  Abstract 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.  
  Address Daejeon, Korea  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-37443-2 Medium  
  Area Expedition Conference ACCV  
  Notes ADAS Approved no  
  Call Number Admin @ si @ RSL2012d Serial 2153  
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