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• 计算机科学 • 上一篇    下一篇

基于C-均值聚类的二层次人像聚类算法

张利彪, 周春光, 李春霞, 孙彩堂, 刘小华, 刘淼   

  1. 吉林大学 计算机科学与技术学院, 长春 130012
  • 收稿日期:2006-05-14 修回日期:1900-01-01 出版日期:2006-08-26 发布日期:2006-11-26
  • 通讯作者: 周春光

Double Hierarchical Face Clustering Based on C-Means

ZHANG Libiao, ZHOU Chunguang, LI Chunxia, SUN Caitang, LIU Xiaohua, LIU Miao   

  1. College of Computer Science and Technology, Jilin University, Changchun 130012, China
  • Received:2006-05-14 Revised:1900-01-01 Online:2006-08-26 Published:2006-11-26
  • Contact: ZHOU Chunguang

摘要: 提出一种基于C-均值聚类的二层次人像聚类算法,解决了传统硬聚类中由于每个数据只能属于某一类而使得处于类边界的数据在检索时结果准确度不高, 以及对高维大数据量数据分类时存在的模糊聚类时间和空间复杂性过大等问题. 该算法为大规模人像数据库检索提供了一种可行的分类方法, 使得分类后的人像数据在有效提高检索速度的同时保证了检索的准确度.

关键词: 聚类分析, 人脸识别, C\|均值聚类, 大库检索

Abstract: This paper presents a double hierarchical face clustering algorithm based on c-means. By means of the algorithm the problems in t he conventional clustering algorithms, namely, (1) every datum could only be classified into one class, which made the result less accurate in clustering the data on the boundary; and, (2) the time and space complexity in fuzzy clustering are e xcessive, unfitting for high dimensional and massive data clustering have been solved. This algorithm provides a feasible clustering method for large scale face database searching, and guarantees the accuracy on increasing the speed of searching.

Key words: clustering, face recognition, c-means clustering, search in large database

中图分类号: 

  • TP391