Title
Object Segmentation Based on Contour-Skeleton Duality
Abstract
This paper presents a novel algorithm for performing integrated object segmentation from a single image. Unlike other state of the art methods which focus on either using contour-based or skeleton-based methods, our approach considers the duality of the two representations (contour/skeleton) and an iterative segmentation procedure that alternates between contour recovery and skeleton fitting. The contour recovery extracts the object contour by adopting the skeleton prior, while the skeleton fitting employs the contour to infer the optimal representation of the object shape. In our approach, the object contour can be directly recovered with no iteration if a detected skeleton is given. Although the proposed method is evaluated for human pose segmentation experiments, it can also be applied to other applications.
Year
DOI
Venue
2014
10.1109/ICPR.2014.438
ICPR
Keywords
DocType
ISSN
object contour extraction,image representation,human pose segmentation,iterative segmentation procedure,image segmentation,pose estimation,contour-skeleton duality,feature extraction,skeleton fitting,optimal object shape representation,object recognition,integrated object segmentation algorithm,duality (mathematics),contour recovery,iterative methods
Conference
1051-4651
Citations 
PageRank 
References 
0
0.34
10
Authors
4
Name
Order
Citations
PageRank
Ling Cai100.34
Fengna Wang2412.94
V. Enescu310510.66
Hichem Sahli447565.19