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in Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR), Anchorage, AL, June 2008 Connected Segmentation Tree
 

Summary: in Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR), Anchorage, AL, June 2008
Connected Segmentation Tree
A Joint Representation of Region Layout and Hierarchy
Narendra Ahuja and Sinisa Todorovic
Beckman Institute, University of Illinois at Urbana-Champaign
{n-ahuja, sintod}@uiuc.edu
Abstract
This paper proposes a new object representation,
called Connected Segmentation Tree (CST), which captures
canonical characteristics of the object in terms of the pho-
tometric, geometric, and spatial adjacency and contain-
ment properties of its constituent image regions. CST is
obtained by augmenting the object's segmentation tree (ST)
with inter-region neighbor links, in addition to their recur-
sive embedding structure already present in ST. This makes
CST a hierarchy of region adjacency graphs. A region's
neighbors are computed using an extension to regions of the
Voronoi diagram for point patterns. Unsupervised learning
of the CST model of a category is formulated as match-
ing the CST graph representations of unlabeled training

  

Source: Ahuja, Narendra - Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign
Todorovic, Sinisa - School of Electrical Engineering and Computer Science, Oregon State University

 

Collections: Computer Technologies and Information Sciences; Engineering