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Multi-feature fusion-based deep learning face recognition method

A multi-feature fusion and deep learning technology, applied in the field of deep learning face recognition based on multi-feature fusion, can solve the problem of low recognition rate

Inactive Publication Date: 2018-01-12
HANGZHOU DIANZI UNIV
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AI Technical Summary

Problems solved by technology

This method works well when the samples are separable, but when the data is not linearly separable, the recognition rate is low

Method used

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  • Multi-feature fusion-based deep learning face recognition method
  • Multi-feature fusion-based deep learning face recognition method
  • Multi-feature fusion-based deep learning face recognition method

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Embodiment Construction

[0076] In order to facilitate those of ordinary skill in the art to understand and implement the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only used to illustrate and explain the present invention, and are not intended to limit this invention.

[0077] please see figure 1 , a kind of deep learning face recognition method based on multi-feature fusion provided by the invention, comprises the following steps:

[0078] Step 1: The number of initialization parameter iterations numepochs=30, each processing data batchsize=1, learning rate=0.001, hidden layer L1=100, hidden layer L2=100.

[0079] Step 2: image feature extraction, including carrying out HOG feature extraction to the original ORL face database and carrying out LBP feature extraction to the original ORL face database;

[0080] [The first fe...

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Abstract

The invention discloses a multi-feature fusion-based deep learning face recognition method. The multi-feature fusion-based deep learning face recognition method comprises performing feature extractionon images in ORL (Olivetti Research Laboratory) through a local binary pattern and an oriented gradient histogram algorithm; fusing acquired textual features and gradient features, connecting the twofeature vectors into one feature vector; recognizing the feature vector through a deep belief network of deep learning, and taking fused features as input of the deep belief network to layer by layertrain the deep belief network and to complete face recognition. By fusing multiple features, the multi-feature fusion-based deep learning face recognition method can improve accuracy, algorithm stability and applicability to complex scenes.

Description

technical field [0001] The invention belongs to the technical field of pattern recognition and deep learning, and relates to a deep learning face recognition method, in particular to a deep learning face recognition method based on multi-feature fusion. Background technique [0002] In recent years, with the rapid development of Internet information, information security has received great attention, and face recognition, as an important biometric information identification method, has many practical applications in the field of information security, such as video surveillance, access Control, intelligent identity authentication, etc. have always been a major research hotspot in the field of machine vision and pattern recognition. Face recognition is an identification technology for identity authentication based on human facial feature information. [0003] The face recognition algorithm is mainly composed of: [0004] ① Method based on geometric features: mainly analyze t...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
Inventor 李训根章舸
Owner HANGZHOU DIANZI UNIV
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