Human face recognition method and device for quickly processing human face shading

A face recognition and human processing technology, applied in the field of computer vision and pattern recognition, can solve problems such as not applicable to real-time scenes, SEC_MRF has high computational complexity, and cannot solve continuous occlusion well

Active Publication Date: 2017-04-19
SOUTH CHINA UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

There are two problems in doing this: (1) The new dictionary has a large number of columns, and it is very time-consuming to solve the sparse coefficient of the test face image on this new dictionary (2) This method cannot solve the ...

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  • Human face recognition method and device for quickly processing human face shading
  • Human face recognition method and device for quickly processing human face shading
  • Human face recognition method and device for quickly processing human face shading

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Embodiment 1

[0101] This embodiment discloses a face recognition method for quickly processing face occlusion, the purpose of which is to have a faster recognition speed under the premise of ensuring a high recognition success rate when recognizing faces with occlusion or noise pollution, so that Better face recognition. A schematic flow chart of a face recognition method for quickly processing face occlusion in this embodiment is as follows figure 1 As shown, it specifically includes the following steps:

[0102] S1. Obtain a test face sample and a standardized learning dictionary. Assuming that the sample image used for testing is y, the dimension is consistent with the training sample image, and it is also converted into an m×1 column vector, then Assuming that the sample images for training have class a, and each class has b sample images, then there are n=a×b sample images for training in total, and the length and width of each image are f and g respectively, then each image The d...

Embodiment 2

[0163]The present invention also provides a face recognition device for quickly processing face occlusion, a structural schematic diagram of a specific implementation is as follows image 3 As shown, the device includes:

[0164] Obtaining module 100, for obtaining test face sample and standardized learning dictionary;

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PUM

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Abstract

The invention discloses a human face recognition method and device for quickly processing human face shading, and the method comprises the steps: obtaining a test human face sample and a standardized learning dictionary; solving a local restriction code of an unshaded part of the test human face sample through employing a target function with the local restriction, and modeling a shaded region of the test human face sample through a Markov random field till the detection is completed; obtaining the sparse representation of the unshaded part of the test human face sample through the target function with l2-normal constraint; generating a reconfigured human face, corresponding to each class, class by class, and solving a reconfiguration error between the reconfigured human face of each class and the test human face sample; searching a corresponding class with the minimum reconfiguration error, determining the class as the class of the test human face sample, and outputting the class. The method can process and recognize a human face which is shaded or polluted by noise, is higher in recognition speed under the condition of guaranteeing the recognition success rate, achieves the better recognition of the human face, and is more suitable for an actual scene.

Description

technical field [0001] The invention relates to the technical field of computer vision and pattern recognition, in particular to a face recognition method and device for quickly processing face occlusion. Background technique [0002] At present, face recognition is one of the hot research issues in the field of computer vision and pattern recognition, and the occlusion problem has become an important and difficult problem in the field of face recognition due to its diversity. [0003] John Wright et al. proposed the Sparse Representation-based classification (SRC) method in 2009. This method believes that each test face image can be linearly combined with the same category of face images in the training sample set. To represent. Therefore, ideally, the encoding coefficients corresponding to training samples of other categories are zero, while the encoding coefficients corresponding to training samples of the same category as the test face samples are not zero, which reflec...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/46G06K9/62
CPCG06V40/168G06V40/172G06V10/40G06V10/513G06F18/28G06F18/24G06F18/214
Inventor 傅予力吴小思张隆琴黄志建向友君
Owner SOUTH CHINA UNIV OF TECH
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