Efficient object recognition using corner features

Jian Cao*, Kan Li, Chunxiao Gao, Qiongxin Liu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

This paper presents a novel method for recognizing objects using corner features. As one of the most important local features, corner contains lots of information with the shape of the objects. Our approach detects corner points from images and describes the objects based on them. The features are highly distinctive, in the sense that a single feature can be correctly matched with high probability against a large database of features from many images. The recognition proceeds by matching individual features to a database of features from known objects using a fast nearest-neighbor algorithm. The performance on the obtained experimental results demonstrates that the proposed method is efficient.

Original languageEnglish
Title of host publicationCIS 2009 - 2009 International Conference on Computational Intelligence and Security
Pages344-348
Number of pages5
DOIs
Publication statusPublished - 2009
Event2009 International Conference on Computational Intelligence and Security, CIS 2009 - Beijing, China
Duration: 11 Dec 200914 Dec 2009

Publication series

NameCIS 2009 - 2009 International Conference on Computational Intelligence and Security
Volume1

Conference

Conference2009 International Conference on Computational Intelligence and Security, CIS 2009
Country/TerritoryChina
CityBeijing
Period11/12/0914/12/09

Keywords

  • CRF
  • Corner point
  • Feature extraction
  • Hausdorff distance
  • Object recognition

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