A New Parallel Hierarchical K-Means Clustering Algorithm for Video Retrieval

被引：1
|
作者：
Liao, Kaiyang [1 ]
Tang, Ziwei [1 ]
Cao, Congjun [1 ]
Zhao, Fan [1 ]
Zheng, Yuanlin [1 ]
机构：
[1] Xian Univ Technol, Fac Printing Packaging Engn & Digital Media Techn, Xian, Shaanxi, Peoples R China
来源：
ADVANCED GRAPHIC COMMUNICATIONS AND MEDIA TECHNOLOGIES | 2017年 / 417卷
基金：
中国国家自然科学基金;
关键词：
Video retrieval; Clustering algorithm; Data mining; Parallel algorithm;
D O I：
10.1007/978-981-10-3530-2_23
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
The K-means clustering algorithm has been widely adopted to build vocabulary in image retrieval. But, the speed and accuracy of K-means still need to be improved. In the manuscript, we propose a New Parallel Hierarchical K-means Clustering (PHKM) Algorithm for Video Retrieval. The PHKM algorithm improves on the K-means as the following ways. First, the Hellinger kernel is used to replace the Euclidean kernel, which improves the accuracy. Second, the multi-core processors based parallel clustering algorithm is proposed. The experiment results show that the proposed PHKM algorithm is very faster and effective than K-means.
引用
收藏
页码：179 / 186
页数：8
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