Human face recognition method based on multi-channel discriminant non-negative matrix factorization under soft label

Abstract

The invention discloses a human face recognition method based on multi-channel discriminant non-negative matrix factorization under a soft label. The problem of low recognition rate for continuously occluded human faces in the prior art is solved. The method provided by the technical scheme comprises the steps that the training data matrix of the k-th channel in a training set is constructed; 2 a local label matrix is acquired from training data; a predictive label matrix and an auxiliary matrix are constructed; a new objective function is formed by introducing the global loss and center loss functions of the predictive label matrix; 3 the objective function is optimized and solved, and a basis matrix, the auxiliary matrix and the predictive label matrix are iteratively updated; 4 the test data matrix of the k-th channel in the training set is constructed, and is projected onto the basis matrix to acquire a projection coefficient matrix; and 5 a local classifier is used to calculate the contribution of each channel, and a global classifier is constructed to acquire the category of a test image. According to the invention, the recognition rate for continuously occluded human faces can be effectively improved, and the human face recognition method can be applied in the fields of identity verification and information security.

Description

technical field [0001] The invention belongs to the technical field of image processing, specifically relates to a face recognition method, and can be applied to the fields of identity verification and information security. Background technique [0002] With the rapid development of computer science and Internet technology, data is rapidly expanding in the form of exponential growth. Although these massive data can provide convenience for life, it also poses a threat to personal information security. Therefore, traditional authentication methods, such as passwords and smart cards, can no longer meet people's security needs. The method of using human biological characteristics such as fingerprints, irises, and smells to verify has the advantages of unique characteristics and difficult forgery. Among all biometric identification technologies, using facial features for identity verification is the most direct and convenient means. These unique advantages make face recognition...

AI Technical Summary

Problems solved by technology

However, the hard label matrix added by this algorithm cannot effectively improve the discriminative ability of the algorithm, so it cannot be used for data classification very well.

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