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Design method of classifier for high-precision face recognitio

A face recognition and design method technology, applied in character and pattern recognition, instruments, computing, etc., can solve the problem that the sparse face recognition algorithm has no explicit expression and cannot use both classified face data and unclassified faces Geometric information of the data and other issues

Inactive Publication Date: 2013-08-28
WENZHOU UNIVERSITY
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Problems solved by technology

[0005] The present invention provides a classifier design method for high-precision face recognition, aiming to solve the problem that the existing face recognition technology cannot make good use of the geometric information of classified face data and unclassified face data at the same time; At the same time, the existing sparse face recognition algorithm has no explicit expression, and cannot perform online real-time face recognition.

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  • Design method of classifier for high-precision face recognitio
  • Design method of classifier for high-precision face recognitio
  • Design method of classifier for high-precision face recognitio

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[0034] Various details involved in the technical solution of the present invention will be described in detail below in conjunction with the accompanying drawings. It should be pointed out that the described embodiments are only intended to facilitate the understanding of the present invention, rather than limiting it in any way.

[0035] Such as figure 1As shown, the present invention provides a kind of classifier design method for high-precision face recognition, comprising the following steps:

[0036] (1) Input face image data and perform normalization processing on the face image data. It is required that the face image data must contain face image samples of known identities, and may contain a large number of face image samples of unknown identities;

[0037] details as follows:

[0038] Input data. any sample x i or x l+j is the data in the form of a column vector converted from a digital image, y i represents the sample x i category information. Among them, l...

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Abstract

The invention provides a design method of a classifier for high-precision face recognition. The design method comprises the following steps of: (1) inputting a vector type face image data set for standardized processing to obtain a face image sample set, wherein the human face image data set must contain the known classes of face image samples and can contain unknown classes of face image samples; (2) utilizing the L1-minimization algorithm to calculate the sparse representation or sparse coding of each face image sample reconstructed by face image samples except the sample; and (3) utilizing the sparse representation or sparse coding of face image samples and the classification information of the classified face image samples to build the optimal model of the classifier, and solving the regularization optimization problem to obtain a classification function. The design method provided by the invention has an explicit way of expression, so that the real-time performance in face recognition application is obviously improved, and the high-precision face recognition is realized under the condition that an image has a great number of noise pixels.

Description

technical field [0001] The invention belongs to the field of machine vision, and in particular relates to a classifier design method for high-precision face recognition. Background technique [0002] Face recognition is one of the most important research topics in the field of pattern recognition research, and it is a very active research direction both at home and abroad. As a typical biometric identification technology, it has special advantages in terms of usability, naturalness, cost, etc. and has been widely recognized. The face recognition system developed by Li Ziqing's group was used in the opening ceremony of the Olympic Games. [0003] At present, the face recognition system with the best performance in the world can meet the requirements of general applications when the user is more cooperative and the image acquisition conditions are relatively stable. This does not mean that face recognition technology has matured. On the contrary, with the development of clos...

Claims

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Application Information

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IPC IPC(8): G06K9/00
Inventor 张笑钦樊明宇王迪
Owner WENZHOU UNIVERSITY
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