Method and device for human face recognition

Abstract

The invention discloses a method and a device for human face recognition. The method comprises steps: through an already-trained first convolutional neural network, a first feature group for a first human face area in a picture is extracted, wherein the first feature group presents human face features in the picture; through an already-trained second convolutional neural network, a second feature group for a second human face area in the picture is extracted, wherein the second human face area is determined by a second area where the human face in the picture is, and the second feature group presents clothes features in the picture; the first feature group and the second feature group are combined, dimension reduction processing is carried out on the feature combination after the combination, and a third feature group is obtained; and according to the cosine distance between the third feature group and already-extracted reference human face features, whether the human face in the picture and the human face corresponding to the reference human face features are the same human face is determined. According to the technical scheme of the invention, the peripheral clothes and ornaments of the user face area can be combined with the user face features for human face recognition, and the human face recognition accuracy is greatly improved.

Description

technical field [0001] The present disclosure relates to the technical field of image recognition, in particular to a face recognition method and device. Background technique [0002] In the process of classifying the user's album by face, it is first necessary to obtain all the photos uploaded by the user's mobile phone, perform face detection on all the photos to extract the face features, and then compare the extracted face features with the classified ones in turn. Face similarity measurement is performed, and photos with similar characteristics are divided into the same face album. In the situation where the user takes multiple photos continuously, if the faces of 7 photos are relatively clear, but the facial features of the other 3 photos cannot be directly extracted due to factors such as posture and lighting, in this case, the faces of the 3 photos Face recognition will fail, which will affect the recognition rate of faces. Contents of the invention [0003] In o...

AI Technical Summary

Problems solved by technology

In the situation where the user takes multiple photos continuously, if the faces of 7 photos are relatively clear, but the facial features of the other 3 photos cannot be directly extracted due to factors such as posture and lighting, in this case, the faces of the 3 photos Face recognition will fail, which will affect the recognition rate of faces

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