Computer Science ›› 2021, Vol. 48 ›› Issue (11A): 275-277.doi: 10.11896/jsjkx.201200102

• Image Processing & Multimedia Technology • Previous Articles     Next Articles

Complete Graph Face Clustering Based on Graph Convolution Network

WANG Wen-bo, LUO Heng-li   

  1. School of Computer Science and Technology,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China
  • Online:2021-11-10 Published:2021-11-12
  • About author:WANG Wen-bo,born in 1996,master.His main research interests include face recognition and face clustering.

Abstract: Face clustering is a method of grouping face images according to different identities,which is mainly used in the fields of face annotation,image management.etc.There is massive redundant data in existing methods.To handle this issue,this paper uses a link prediction method based on complete graph constraint and context relationship.The clustering algorithm is based on graph convolution network for link prediction,combined with complete graph constraints to filter data,and the link relationship is constantly updated in the process of prediction.Experimental results show that the face clustering method combined with complete graph constraint can reduce redundant data,speed up the operation,and improve the accuracy of clustering.Thus it improves the overall performance of clustering.

Key words: Complete graph constraint, Face clustering, Graph convolution network, Link prediction

CLC Number: 

  • TP391.4
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