Face recognition method and device based on key point region feature fusion

A regional feature and face recognition technology, which is applied in character and pattern recognition, instruments, computer parts, etc., can solve the problems of insufficient accuracy and robustness of face recognition, low classifier classification ability, and incomplete feature extraction and other problems, to achieve the effect of robustness and accuracy, accurate description, and improved classification ability

Active Publication Date: 2019-06-07
北京云和互动信息技术有限公司
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Problems solved by technology

[0004] To this end, the embodiment of the present invention provides a face recognition method and device based on key point region feature fusion to solve the problem of low recognition accuracy of existing face recognition methods and the lack of features of face recognition methods based on convolutional neural networks. The extraction is incomplete and incomplete, which leads to the problem of low classification ability of the classifier and insufficient accuracy and robustness of face recognition

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  • Face recognition method and device based on key point region feature fusion

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Embodiment 1

[0037] like figure 1 As shown, the embodiment of the present invention proposes a face recognition method based on key point region feature fusion, the method comprising:

[0038] S100. Perform data preprocessing on a training set or a test set. In this embodiment, the training set uses the MS-Celeb-1M data set.

[0039]MSR IRC is currently one of the largest and highest-level image recognition competitions in the world. MS-Celeb-1M is the public data set of this competition. From 1M celebrities, according to their popularity, select 100K individuals, and then use The search engine, according to the selected 100K individuals, each person searches about 100 pictures, a total of 100K×100=10M pictures. The training set includes 1,000 celebrities. These 1,000 celebrities are randomly selected from 1M celebrities, and after labeling, each celebrity has about 20 pictures, which cannot be found on the Internet.

[0040] Specifically, data preprocessing on the training set or test ...

Embodiment 2

[0054] Corresponding to Embodiment 1 above, this embodiment proposes a face recognition device based on feature fusion of key point regions, which includes:

[0055] The preprocessing module is used to perform data preprocessing on the training set or test set.

[0056] The network building module is used to build a convolutional neural network model.

[0057] The training module is used to use the preprocessed training set to train the convolutional neural network model, extract the key point region features of the human face and perform fusion.

[0058] The test module is used to test the convolutional neural network model by using the preprocessed test set.

[0059] Further, the preprocessing module includes:

[0060] Data cleaning unit, used for data cleaning of training set or test set;

[0061] The face detection unit is used to detect faces in the face pictures in the training set or test set, and extract the face images;

[0062] The face alignment unit is configur...

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Abstract

The embodiment of the invention discloses a face recognition method and device based on key point region feature fusion. The method comprises the following steps: carrying out data preprocessing on atraining set or a test set; constructing a convolutional neural network model; training the convolutional neural network model by using the preprocessed training set, extracting face key point regionfeatures, and fusing the face key point region features; and testing the convolutional neural network model by using the preprocessed test set. The extracted features of the face key point area are fused by using a convolutional neural network; the defect that the traditional face recognition method is sensitive to various uncertain interferences such as illumination difference, facial expression,occlusion and the like is overcome; the global features and the invariant features of the human face are comprehensively considered, the recognition model has higher robustness and accuracy, the relation between different features is enhanced, the extracted features are more perfect and complete, the human face information can be described more accurately, and the classification capacity of a classifier is improved.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of computer vision processing, and in particular to a face recognition method and device based on feature fusion of key point regions. Background technique [0002] Computer vision is currently the hottest research direction in the field of deep learning. In particular, more and more computer vision technologies have been applied. One of the most widely used technologies is face recognition technology, which is also used in biological A variety of technologies in the field of feature recognition are constantly updating and iterating the technologies that survive after competition and elimination. At present, face recognition methods are mainly divided into two categories, one is representation-based methods, and the other is feature-based methods. The basic idea of ​​the appearance-based method is to convert the two-dimensional face image to another space, and then analyze the face pat...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
Inventor 安玉山
Owner 北京云和互动信息技术有限公司
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