Context-based adaptive filtering of interest points in image retrieval

Phuong Giang Nguyen, Hans Jørgen Andersen

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

2 Citations (Scopus)

Abstract

Interest points have been used as local features with success in many computer vision applications such as image/video retrieval and object recognition. However, a major issue when using this approach is a large number of interest points detected from each image and created a dense feature space. This influences the processing speed in any runtime application. Selecting the most important features to reduce the size of the feature space will solve this problem. Thereby this raises a question of what makes a feature more important than the others? In this paper, we present a new technique to choose a subset of features. Our approach differs from others in a fact that selected feature is based on the context of the given image. Our experimental results show a significant reduction rate of features while preserving the retrieval performance.
Original languageEnglish
Title of host publicationProceedings of the 2009 Ninth International Conference on Intelligent Systems Design and Applications
Number of pages5
PublisherIEEE Computer Society Press
Publication date2009
Pages529-534
ISBN (Print)9780769538723
Publication statusPublished - 2009
EventIEEE proceeding of the International Conference on Intelligent Systems Design and Applications - Pisa, Italy
Duration: 30 Nov 20092 Dec 2009
Conference number: 9

Conference

ConferenceIEEE proceeding of the International Conference on Intelligent Systems Design and Applications
Number9
Country/TerritoryItaly
CityPisa
Period30/11/200902/12/2009

Keywords

  • Image retrieval
  • interest points detection

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