ICIP 2006, Atlanta, GA
 

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Atlanta Conv. & Vis. Bureau

 

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Paper Detail

Paper:MA-P4.4
Session:Image Registration/Alignment and Mosaicking
Time:Monday, October 9, 09:40 - 12:20
Presentation: Poster
Topic: Interpolation and Super-Resolution: Registration / alignment
Title: IMAGE ALIGNMENT USING LEARNING PRIOR APPEARANCE MODEL
Authors: Ayman El-Baz; University of Louisville 
 Aly A. Farag; University of Louisville 
 Georgy Gimel'farb; University of Auckland 
 Alaa Abdel-Hakim; University of Louisville 
Abstract: A new approach to align an image of a textured object with a given prototype is proposed. Visual appearance of the images, after equalizing their signals, is modeled with a Markov-Gibbs random field with pairwise interaction. Similarity to the prototype is measured by a Gibbs energy of signal cooccurrences in a characteristic subset of pixel pairs derived automatically from the prototype. An object is aligned by an affine transformation maximizing the similarity by using an automatic initialization followed by gradient search. Experiments confirm that our approach aligns complex objects better than popular conventional algorithms.