Region Matching with Missing Parts
Author(s) -
Alessandro Duci,
Anthony Yezzi,
Sanjoy K. Mitter,
Stefano Soatto
Publication year - 2002
Publication title -
lecture notes in computer science
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.249
H-Index - 400
eISSN - 1611-3349
pISSN - 0302-9743
DOI - 10.1007/3-540-47977-5_4
Subject(s) - inpainting , affine transformation , missing data , artificial intelligence , mathematics , partial differential equation , pattern recognition (psychology) , grayscale , computer vision , matching (statistics) , computer science , image (mathematics) , algorithm , geometry , mathematical analysis , statistics
©2002 Springer Verlag. The original publication is available at www.springerlink.comDOI: 10.1007/3-540-47977-5_4We present a variational approach to the problem of registering planar shapes despite missing parts. Registration is achieved through the evolution of a partial differential equation that simultaneously estimates the shape of the missing region, the underlying “complete shape” and the collection of group elements (Euclidean or affine) corresponding to the registration. Our technique applies both to shapes, for instance represented as characteristic functions (binary images), and to grayscale images, where all intensity levels evolve simultaneously in a partial differential equation. It can therefore be used to perform “region inpainting” and to register collections of images despite occlusions. The novelty of the approach lies on the fact that, rather than estimating the missing region in each image independently, we pose the problem as a joint registration with respect to an underlying “complete shape” from which the complete version of the original data is obtained via a group action
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