Extraction of robust visual phrases using graph mining for image retrieval

Jun Bin Yeh, Chung Hsien Wu

研究成果: Conference contribution

8 引文 斯高帕斯(Scopus)

摘要

For the images of an objects with multi-viewpoints, the visual words in a visual phrase may be covered by the object and thus degrades the visual phrase extraction performance. This paper presents an approach to robust visual phrase extraction using graph mining for content-based image retrieval. In this study, the concurrent appearance of two visual words can be estimated over all of the category-related images in a database. The appearance frequencies of the visual words at each image are then used to construct a relation graph of visual words. Graph mining is utilized to mine the frequent dense subgraphs from the visual word relation graphs to extract the visual phrases. Experiments were conducted on the Caltech101 database and the experimental results show that the extracted visual phrases are robust to achieve a better retrieval performance than the pair-wise visual phrase approach.

原文English
主出版物標題ISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems
主出版物子標題Nano-Bio Circuit Fabrics and Systems
頁面3681-3684
頁數4
DOIs
出版狀態Published - 2010 八月 31
事件2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems, ISCAS 2010 - Paris, France
持續時間: 2010 五月 302010 六月 2

出版系列

名字ISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems

Other

Other2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems, ISCAS 2010
國家France
城市Paris
期間10-05-3010-06-02

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Electrical and Electronic Engineering

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