Three-dimensional face recognition method based on semantic alignment multi-region template fusion

Abstract

The invention provides a three-dimensional face recognition method based on semantic alignment multi-region template fusion, which comprises the following steps of: 1, determining a data set of registered faces and test faces in a three-dimensional face database; 2, preprocessing all registered and to-be-identified three-dimensional face models, and performing dense alignment on the preprocessed three-dimensional face models and the reference model; 3, pre-dividing the face region into a plurality of template regions which do not contain expression influence and can be overlapped; 4, for eachtemplate area, directly calculating a similarity value between the template areas on the three-dimensional structure of the human face; And 5, independently voting each region according to the similarity value, synthesizing a plurality of region matching results, and determining a final matching result by adopting a majority voting mode. According to the face recognition method provided by the invention, similarity prediction is carried out by utilizing mutual independence of the multi-template areas, the dependence of an algorithm on accurate division of a single area is reduced, and meanwhile, a multi-area template common voting strategy is adopted, so that certain robustness is also achieved on expressions and other factors influenced by the areas.

Description

technical field [0001] The invention belongs to the technical field of image processing and pattern recognition, and more specifically relates to a three-dimensional face recognition method based on semantically aligned multi-region template fusion. Background technique [0002] Face recognition has broad application prospects in public security criminal investigation, national security, market finance and many other fields. However, in view of the deformable nature of the 3D face itself and its susceptibility to different expression changes, the development of face recognition algorithms that are robust to expressions has always been a research hotspot and difficult issue in the field of 3D face recognition. [0003] At present, expression-robust 3D face recognition methods are mainly divided into statistical model methods, equivalent deformation model methods and region-based methods. Among them, the statistical model method is to describe the facial soft tissue deformati...

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Problems solved by technology

[0007] Aiming at the deficiencies of the prior art, the present invention proposes a 3D face recognition method based on semantic alignment and multi-region fusion, which solves the problem that the region-based method is relatively dependent on the accuracy of region division and does not make full use of the entire face region

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