Face recognition method based on cosine loss non-constraint conditions

A face recognition, unconstrained technology, applied in the field of image processing, can solve the problems of recognition accuracy decline, loss, etc.

Active Publication Date: 2020-07-10
TIANJIN UNIVERSITY OF TECHNOLOGY
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Problems solved by technology

Regarding posture issues, such as the loss of facial feature information due to the rotation of the face, the current recognition algorithm mainly focuses on frontal and quasi-frontal face information imag...

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[0038] In order to explain in detail the technical content, structural features, achieved goals and effects of the technical solution, the following will be described in detail in conjunction with specific embodiments and accompanying drawings.

[0039] refer to figure 1 As shown, it is a flow chart of the face recognition method. A kind of face recognition method based on cosine loss unconstrained condition, it comprises the following steps,

[0040] S1. Obtain an image to be recognized, perform multi-scale transformation on the image to be recognized, and obtain an image pyramid.

[0041] In an unconstrained environment, face detection and recognition are very challenging for different poses, lighting and occlusions. The specific implementation plan is mainly face detection and correction, as well as the training of the face recognition model. For the detection and correction module, a deep cascade multi-task framework is proposed, so a multi-task cascade convolutional neu...

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Abstract

The invention belongs to the technical field of image processing, and particularly relates to a face recognition method based on cosine loss non-constraint conditions. The method comprises the following steps: S1, obtaining a to-be-recognized image, and performing multi-scale transformation on the to-be-recognized image to obtain an image pyramid; S2, inputting the image pyramid obtained in the step S1 into an MTCNN network, and processing the image by the MTCNN network to obtain facial feature points; S3, performing face correction according to the facial feature points in the step S2; S4, training an Inception-ResnetV1 convolutional neural network by using the data processed in the step S3, training a classifier model by using a cosine loss function as a supervision signal to obtain a feature extraction model, and performing verification and recognition of face data by using the feature extraction model.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a face recognition method based on cosine loss and non-constrained conditions. Background technique [0002] Face recognition is an important biometric technology for identity authentication, which has been widely used in military, financial, public safety and daily life fields. Although the research on the human face has lasted for fifty years, it is still affected by various external factors such as different light intensities, changes in facial posture and expression, partial occlusion of the face, and age. influences. Face recognition technology is mainly a kind of identity authentication through the facial geometric features of the face. Regarding posture issues, such as the loss of facial feature information due to the rotation of the face, the current recognition algorithm mainly focuses on frontal and quasi-frontal face information images to perform...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06N3/04G06N3/08G06K9/62
CPCG06N3/08G06V40/168G06V40/172G06N3/045G06F18/214
Inventor 董恩增乔逸凡佟吉钢于航张达
Owner TIANJIN UNIVERSITY OF TECHNOLOGY
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