In this paper, we investigate the use of discriminant techniques in the elastic graph matching (EGM) algorithm. First we use discriminant analysis in the feature vectors of the nodes in order to find the most discriminant features. The similarity measure for discriminant feature vectors and the node deformation are combined in a discriminant manner in order to form a local similarity measure between nodes. Moreover, the local similarity values at the nodes of the elastic graph, are weighted by coefficients that are also derived by some discriminant analysis in order to form a total similarity measure between faces. We illustrate the improvements in performance in frontal face verification using a modified multiscale morphological analysis.
Zafeiriou et al. REF used eigen-analysis to find the most discriminant features from the jets and proposed a new similarity measure for these.
Exploiting discriminant information in elastic graph matching
IEEE International Conference on Image Processing 2005
IEEE International Conference on Image Processing 2005
Computer Science