Cross view angle face recognition method based on structuralized dictionary domain transfer

Abstract

The invention discloses a cross view angle face recognition method based on structuralized dictionary domain transfer. The method comprises the steps that S1, trained sub-dictionaries having discrimination performance on sample categories are connected in series to form a structuralized source domain dictionary; S2, a target domain and a plurality of intermediate domain dictionaries are learned; S3, image face codes of the source domain and the target domain, the source domain dictionary, the target domain dictionary and the intermediate domain dictionaries are calculated, source domain reconstruction images of face images of the source domain and the target domain, target domain reconstruction images and intermediate domain reconstruction images are obtained and connected in series to form the domain sharing characteristic of the face images of the source domain and the domain sharing characteristic of the face images of the target domain; S4, according to the domain sharing characteristic of the face images of the source domain, a support vector machine model is trained for each sample category in a face set of the source domain, the domain sharing characteristic of the face images of the target domain is input into the support vector machine models of all categories, and the category corresponding to the support vector machine model with the highest score is defined as the category of the face images of the target domain.

Description

technical field [0001] The invention belongs to the technical field of cross-view face recognition, and in particular relates to a cross-view face recognition method based on structured dictionary domain transfer. Background technique [0002] At present, most automatic face recognition systems can achieve high recognition performance in frontal view. However, the face pictures acquired in practical application scenarios are generally in various viewing angles, which will greatly degrade the performance of the face recognition system. The difficulty of cross-view face recognition is mainly that the change of face view is in 3D space, while the face image only captures 2D appearance features. As the viewing angle changes, different face parts appear in the image. This leads to a special phenomenon: face images of different identities with similar perspectives are more similar than face images of the same identity with different perspectives. The differences caused by viewp...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to solve the problem of large differences in the distribution of face images of the same identity and different perspectives in cross-view face recognition. Therefore, the purpose of the present invention is to provide a cross-view face based on structured dictionary domain transfer. recognition methods

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