Face clustering method, device and system and storage medium

Abstract

The embodiment of the invention provides a face clustering method, device and system and a storage medium. The method includes: acquiring a plurality of face images; detecting face quality of target faces in the plurality of face images to obtain face quality data of the plurality of face images; extracting features of target faces in at least partial face images in the plurality of face images toobtain face feature data of the at least partial face images; and carrying out clustering on the at least partial face images according to the face feature data and the face quality data of the at least partial face images. According to the face clustering method, device and system and the storage medium of the embodiment of the invention, the face features are considered in clustering, the facequality is also considered, and impacts of poor face quality or large face quality difference on a clustering effect are enabled to be effectively reduced in a clustering process. The face clusteringmethod has the characteristics of a high accuracy rate, a high recall rate, high reliability and the like.

Description

technical field [0001] The present invention relates to the field of image processing, and more particularly relates to a face clustering method, device, system and storage medium. Background technique [0002] Face clustering refers to the clustering of unmarked face images based on whether the people in the image are the same person or not, and the face images belonging to the same person are merged into one group, and the faces that do not belong to the same person are clustered. Images are separated into different groups. Face clustering technology is widely used in many fields such as album management and stranger recognition. [0003] There are many existing face clustering methods. Usually, the features that can represent the face in this face image are extracted from the face image, and then the features of each face image are compared and compared according to a certain algorithm. polymerization. The existing face clustering methods simply consider the face featu...

AI Technical Summary

Problems solved by technology

The existing face clustering methods simply consider the face feature factors, but the quality of the face image (or the face in the face image) will have a great impact on the comparison between face features

When the quality of the face images participating in the clustering is relatively poor and / or there are large differences in the quality of different face images, the clustering effect of the existing face clustering methods cannot be guaranteed

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