Face recognition method and device, electronic equipment and storage medium
A face recognition and to-be-recognized technology, applied in character and pattern recognition, instruments, computer parts, etc., can solve the problems of reduced model accuracy, loss of accuracy, and changes in the aspect ratio of the face, so as to improve the accuracy, The effect of improving recall
Inactive Publication Date: 2019-10-11
北京蓝城兄弟文化传媒有限公司
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[0003] In the field of computer vision, target detection based on deep learning technology is divided into two categories. The first category is a two-level detection method based on candidate regions. This method uses a candidate region generation network that shares features with the classification network. Find a number of candidate areas in the network, and then use the correction network to classify and correct the candidate areas; the second type is a first-level detection method that directly predicts the position and category of the target on the feature map. Directly define several basic frames, which improves the real-time performance of the algorithm but loses precision
[0004] In the face detection problem, the aspect ratio of the face does not change much. The more common method is to use the sliding window method to directly generate candidate frames on the image pyramid, and then classify and correct these candidate frames. This method is due to the There are many frames, and the network is usually shallow; in recent years, there are also methods based on one-level detection methods, which usually use multi-layer features for detection, which reduces the number of missed detections, but the accuracy of the model is reduced
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[0030] Various exemplary embodiments, features, and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numbers in the figures indicate functionally identical or similar elements. While various aspects of the embodiments are shown in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.
[0031] The word "exemplary" is used exclusively herein to mean "serving as an example, embodiment, or illustration." Any embodiment described herein as "exemplary" is not necessarily to be construed as superior or better than other embodiments.
[0032] The term "and / or" in this article is just an association relationship describing associated objects, which means that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist simultaneously, and there exists alone B these three situations. In addition, the term "at least one" herein mean...
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The invention relates to a face recognition method and device, electronic equipment and a storage medium, and the method comprises the steps: carrying out the image type classification of a to-be-processed image, obtaining a to-be-recognized face image comprising a face image region, recognizing the to-be-recognized face image, and obtaining a face recognition result. Through the face recognitionmethod, the recall rate of the face recognition model is improved, and the accuracy of the face recognition result is improved.
Description
technical field [0001] The invention relates to the technical field of artificial intelligence, in particular to a face recognition method and device, electronic equipment and a storage medium. Background technique [0002] Face detection is a branch of target detection. Compared with general target detection, face detection has fewer target categories, and higher accuracy and recall are required in application scenarios. [0003] In the field of computer vision, target detection based on deep learning technology is divided into two categories. The first category is a two-level detection method based on candidate regions. This method uses a candidate region generation network that shares features with the classification network. Find a number of candidate areas in the network, and then use the correction network to classify and correct the candidate areas; the second type is a first-level detection method that directly predicts the position and category of the target on the ...
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IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/165G06V40/172G06F18/214G06F18/2415
Inventor 刘翔宇王英杰刘元晨
Owner 北京蓝城兄弟文化传媒有限公司