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Titolo:
A Bayesian similarity measure for deformable image matching
Autore:
Moghaddam, B; Nastar, C; Pentland, A;
Indirizzi:
Mitsubishi Elect Res Lab, Cambridge, MA 02139 USA Mitsubishi Elect Res Lab Cambridge MA USA 02139 , Cambridge, MA 02139 USA LookThatUp, F-75002 Paris, France LookThatUp Paris France F-75002LookThatUp, F-75002 Paris, France MIT, Media Lab, Cambridge, MA 02139 USA MIT Cambridge MA USA 02139MIT, Media Lab, Cambridge, MA 02139 USA
Titolo Testata:
IMAGE AND VISION COMPUTING
fascicolo: 5, volume: 19, anno: 2001,
pagine: 235 - 244
SICI:
0262-8856(20010401)19:5<235:ABSMFD>2.0.ZU;2-9
Fonte:
ISI
Lingua:
ENG
Soggetto:
DEFORMATIONS; MODELS;
Keywords:
face recognition; image matching; image warping; deformable surfaces; density estimation; Bayesian analysis; principal component analysis; eigenfaces;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
30
Recensione:
Indirizzi per estratti:
Indirizzo: Moghaddam, B Mitsubishi Elect Res Lab, Cambridge, MA 02139 USA Mitsubishi Elect Res Lab Cambridge MA USA 02139 MA 02139 USA
Citazione:
B. Moghaddam et al., "A Bayesian similarity measure for deformable image matching", IMAGE VIS C, 19(5), 2001, pp. 235-244

Abstract

We propose a probabilistic similarity measure for direct image matching based on a Bayesian analysis of image deformations. We model two classes of variation in object appearance: intra-object and extra-object. The probability density functions for each class are then estimated from training data and used to compute a similarity measure based on the a posteriori probabilities. Furthermore, we use a novel representation for characterizing image differences using a deformable technique for obtaining pixel-wise correspondences. This representation, which is based on a deformable 3D mesh in XYI-space, is then experimentally compared with two simpler representations: intensity differences and optical Row. The performance advantage of our deformable matching technique is demonstrated using a typically hard test set drawn from the US Army's FERET face database. (C) 2001 Elsevier Science B.V. All rights reserved.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 19/01/20 alle ore 20:07:28