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

页码：179 / 186

页数：8

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