Bi-visual-angle face identification method based on multi-local correlation characteristic learning

A related feature, face recognition technology, applied in character and pattern recognition, computer parts, instruments, etc., can solve the problems of complex nonlinear structure of face data, difficult nonlinear structure of data, affecting the accuracy of face recognition, etc.

Active Publication Date: 2016-08-24
河北暮果信息科技有限公司
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Problems solved by technology

However, all these CCA methods based on local neighbor information only consider a neighbor relationship of samples
In the practical application of face recognition, the actual collected face data often ha

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  • Bi-visual-angle face identification method based on multi-local correlation characteristic learning
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  • Bi-visual-angle face identification method based on multi-local correlation characteristic learning

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Embodiment Construction

[0068] The specific implementation manner of the invention will be further described below in conjunction with the accompanying drawings and examples. The following examples are only used to illustrate the present invention, but not to limit the scope of the present invention.

[0069] The next example is for the AR face database, which consists of more than 4,000 color images of 126 people (70 males and 56 females), with 26 images per person, divided into two groups, 13 in each group, shooting The time interval is two weeks, reflecting the changes in facial expression, illumination and occlusion respectively. In the next experiment, the present invention uses a subset of the database, a total of 120 people (65 men, 55 women), each with 14 images without occlusion. When randomly selecting 6 images of each person in the data as training images, the specific implementation steps of the present invention are:

[0070] Step 1: Randomly select 6 images from 14 unoccluded images o...

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Abstract

The invention discloses a bi-visual-angle face identification method based on multi-local correlation characteristic learning. Multiple local information in correlation characteristic learning is used to better know real non-linear structures among data, so that the face identification accuracy is improved. The realization process includes the steps of determining a plurality of local blocks of each training sample, constructing a uniform optimization framework of related characteristic learning and multi-local fusion, solving the correlation projection direction and multi-local fusion coefficient through alternative iteration, conducting feature extraction and characteristic fusion for training and testing samples, and using the nearest neighbor classifier for identification. Compared with the prior art, the bi-visual-angle face identification method is more effective and robust.

Description

technical field [0001] The invention relates to the fields of pattern recognition, image processing, etc., and in particular to a dual-view face recognition method based on multi-local correlation feature learning. Background technique [0002] Face recognition is a kind of biometric identification, which has the characteristics of non-contact collection, concealable collection, long-distance transmission, fast tracking and network monitoring. It has more advantages than other biometric recognition such as fingerprint recognition, iris recognition and gene recognition. Face recognition has a wide range of application values. It can be applied to customs monitoring, criminal tracking, file management, customer identification, human-computer interaction system certification, job inspection, multimedia data retrieval, information security, machine vision, virtual reality technology, etc. , has significant economic value and social benefits. [0003] Human faces have rich expre...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/161G06V40/172G06F18/24147
Inventor 葛洪伟苏树智李鹏朱嘉钢
Owner 河北暮果信息科技有限公司
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