A Novel Fast Affinity Propagation Based Visual Word Clustering Algorithm

被引：0

作者：

Jian, Zhao ^{[1
]}

Jian, Jia ^{[1
]}

Duan, Xie ^{[2
]}

Ning, Feng ^{[1
]}

Yu, Xie ^{[1
]}

机构：

[1] NW Univ Xian, Sch Informat Sci & Technol, Xian 710069, Peoples R China

[2] Xian Univ Posts & Telecommun, Sch Elect Engn, Xian 710121, Peoples R China

来源：

JOURNAL OF COMPUTATIONAL AND THEORETICAL NANOSCIENCE | 2014年 / 11卷 / 11期

基金：

中国国家自然科学基金;

关键词：

Indexing Structure; Vocabulary Tree; Visual Word; Affinity Propagation Clustering;

D O I：

10.1166/jctn.2014.3634

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

The weaknesses of k-means clustering would result in deviation of the vocabulary tree structure. In this paper, we developed an improved affinity propagation clustering algorithm based vocabulary tree structure. Three datasets were used to test the tasks: the Corel dataset, the LabelMe dataset and the Caltech-101 dataset. The experimental result shows that this new build method for vocabulary tree offers not only compute vocabulary tree set faster, but also improve the retrieval accuracy.

引用

页码：2258 / 2262

页数：5

共 16 条

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