Robust keypoint detection using dynamics

Miguel Angel Cataño, Juan Climent

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

Abstract

In this paper we present a keypoint detector based on the bimodality of the histograms of oriented gradients (HOGs). We compute the bimodality of each HOG, and a bimodality image is constructed from the result of this bimodality test. The maxima with highest dynamics of the image obtained are selected as robust keypoints. The bimodality test of HOGs used is also based on dynamics. We compare the results obtained using this method with a set of well-known keypoint detectors.

Original languageEnglish
Title of host publicationMathematical Morphology and Its Applications to Signal and Image Processing - 11th International Symposium, ISMM 2013, Proceedings
Pages402-412
Number of pages11
DOIs
StatePublished - 2013
Event11th International Symposium on Mathematical Morphology, ISMM 2013 - Uppsala, Sweden
Duration: 27 May 201329 May 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7883 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Symposium on Mathematical Morphology, ISMM 2013
Country/TerritorySweden
CityUppsala
Period27/05/1329/05/13

Keywords

  • dynamics
  • histograms of oriented gradients
  • keypoint detection
  • test of bimodality

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