A Bayesian similarity measure for direct image matching
- 1 January 1996
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 2 (5) , 350-358 vol.2
- https://doi.org/10.1109/icpr.1996.546848
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 flow. 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.Keywords
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