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Method for identifying second level human face with weighted collaborative representation and linear representation classification combined

A linear representation and face recognition technology, applied in the field of secondary face recognition, can solve problems such as being susceptible to noise interference and high image requirements, and achieve the effects of improving efficiency, good recognition effect, and high recognition rate

Inactive Publication Date: 2016-07-20
NANTONG SHIPPING COLLEGE
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Problems solved by technology

In the application of face recognition, both the calculation efficiency and the recognition rate are very good, but the requirements for the image are relatively high, and it is susceptible to noise interference.

Method used

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  • Method for identifying second level human face with weighted collaborative representation and linear representation classification combined
  • Method for identifying second level human face with weighted collaborative representation and linear representation classification combined
  • Method for identifying second level human face with weighted collaborative representation and linear representation classification combined

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Embodiment Construction

[0030] The present invention will be described in further detail below through examples, and the following examples are explanations of the present invention and the present invention is not limited to the following examples.

[0031]The two-level face recognition method based on the fusion of weighted collaborative representation and linear representation classification of the present invention is based on the lower time complexity of the CRC algorithm, and can still obtain a higher recognition rate through collaboration under the premise of sacrificing a certain sparseness of samples. Therefore, a new method is proposed in combination with CRC. Considering that each training sample has a certain local similarity with the test sample, their contribution to classification and recognition depends on the degree of similarity, and this similarity can be calculated by the Euclidean distance, that is, the error between each training sample and the test sample, as To avoid the pheno...

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Abstract

The invention discloses a method for identifying second level human face with weighted collaborative representation and linear representation classification combined. The method combines CRC and LRC. The method includes the following steps: firstly based on PCA, reducing dimensions of all the image samples so as to reduce computing complexity; taking different contributions of sample local similarity prior information on identifying classifications into consideration, constructing a weighted matrix and embedding to the CRC, proposing the weighted CRC, and then based on the weighted CRC, in accordance with reconstruction residual error ordering, reserving plural types of training samples with a greater similarity for LRC so as to realize secondary classification identification. The method reduces classification objects, which makes identification more accurate, and substantially reduces time for identification.

Description

technical field [0001] The invention relates to a face recognition method, in particular to a two-level face recognition method based on the fusion of weighted collaborative representation and linear representation classification. Background technique [0002] In today's digital information age, with the rapid development of the Internet, the security of various information resources is a very important issue, and access control security protection measures have been adopted on many occasions. Among them, identification based on physiological characteristics, such as face recognition and fingerprint recognition, are widely used because of their real-time and convenience. Nowadays, in the field of transportation, especially airports and stations with high security requirements, real-time security monitoring is carried out through computer vision systems, and any extraction and analysis of relevant features in videos is based on human faces. How to detect and recognize faces ...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/172G06F18/214
Inventor 施志刚
Owner NANTONG SHIPPING COLLEGE
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