Non-restricted environment face verification method based on block depth neural network

Abstract

The invention discloses a non-restricted environment face verification method based on block depth neural network. The method comprises the following steps of (1) detecting a face area at which a face image is input, and normalizing the face area; (2) dividing the normalized face area into a plurality of non-overlapping rectangular subimages, extracting feature of each subimage, and performing dimensionality reduction and normalization processing; (3) building one depth neural network for each subimage according to the extracted subimage features, wherein the subimage features are changed into new features after being input into network; (4) according to paired face image data and the depth neural network group, optimizing structure parameter of the depth neural network by restraining foreign separability and congeneric compactness of the changed new features; and (5) inputting paired face images into the optimized depth neural network group, calculating distance between the new features, and verifying the face pair.

Description

technical field [0001] The invention belongs to the technical field of face recognition, and in particular relates to an unrestricted environment face verification method based on a block deep neural network. Background technique [0002] The goal of face verification is to verify the identity claimed by a person. Usually a pair of face pictures is provided, and it is necessary to judge whether the pair of pictures are from the same person or different people. Face pictures in unrestricted environments usually contain complex background changes, including lighting, occlusion, and changes in their own posture and expression. These influences may make a difference that is greater than the difference in the picture due to identity changes. Therefore, in an unconstrained environment, different person image pairs with the same pose or the same lighting conditions will often be verified as coming from the same person; while image pairs of the same person will be verified as comi...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to solve the problems of poor low-level feature expression ability in complex environments and difficult training of deep neural networks for high-dimensional input. For this reason, the present invention provides a face verification method based on block deep neural networks in an unrestricted environment

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