Elastic Bunch Graph Matching is a face recognition algorithm that is distributed with CSU’s Evaluation of Face Recognition Algorithms System. The algorithm is modeled after the Bochum/USC face recognition algorithm used in the FERET evaluation. The algorithm recognizes novel faces by first localizing a set of landmark features and then measuring similarity between these features. Both localization and comparison uses Gabor jets extracted at landmark positions. In localization, jets are extracted from novel images and matched to jets extracted from a set of training/model jets. Similarity between novel images is expressed as function of similarity between localized Gabor jets corresponding to facial landmarks. A study of how accurately a landmark is localized using different displacement estimation methods is presented. The overall performance of the algorithm subject to changes in the number of training/model images, choice of specific wavelet encoding, displacement estimation technique and Gabor jet similarity measure is explored in a series of independent tests. Several findings were particularly striking, including results suggesting that landmark localization is less reliable than might be expected. However, it is also striking that this did not appear t
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