Multi-task deep feature space attitude face recognition method

A deep feature and face recognition technology, which is applied in the fields of computer vision and artificial intelligence, can solve the problems of difficult face recognition rate and affecting face recognition rate, etc.
CN110276274AActive Publication Date: 2019-09-24SOUTHEAST UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
SOUTHEAST UNIV
Publication Date
2019-09-24

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Abstract

The invention discloses a multi-task depth feature space attitude face recognition method, which comprises the following steps: firstly, carrying out angle measurement on an attitude face image, and extracting image depth space features by utilizing a residual network; then, adding a residual transformation mapping module to realize transformation from the side face depth feature to the front face depth feature, so that a main task of the network is formed; then, adding a module on the basis of an original residual transformation mapping module to realize reconstruction of original side face depth characteristics so as to realize feedback which is a secondary task of the network; and finally, using the cosine similarity to measure the similarity between the to-be-compared face and the depth feature representation of all people in the database, so that face authentication recognition is carried out. According to the method, the robust representation of the front face depth space feature can be obtained according to the side face depth space feature, so that the side face recognition rate is greatly improved, and the method has a very good application prospect in attitude face detection and recognition.
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Description

technical field

[0001] The invention belongs to the technical field of computer vision and artificial intelligence, and relates to a face recognition method, in particular to a multi-task deep feature space gesture face recognition method. Background technique

[0002] Face recognition technology is one of the hot research topics in the fields of contemporary artificial intelligence, pattern recognition, and computer vision. Face recognition technology is used in a wide range of fields, such as public security, e-commerce and information security. In the face recognition detection in practical applications, it is concluded that the angle and posture factors are the main factors affecting the face recognition results. When the input face image is a side face image with a large deflection angle, the performance of many conventional face recognition algorithms will drop significantly, resulting in a significant drop in recognition rate. Therefore, it is of great value and sig...

Claims

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