Bifocal matching using multiple geometrical solutions

Miguel Carrasco, Domingo Mery

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

2 Scopus citations

Abstract

Determining point-to-point correspondence in multiple images is a complex problem because of the multiple geometric and photometric transformations and/or occlusions that the same point can undergo in corresponding images. This paper presents a method of point-to-point correspondence analysis based on the combination of two techniques: (1) correspondence analysis through similarity of invariant features, and (2) combination of multiple partial solutions through bifocal geometry. This method is quite novel because it allows the determination of point-to-point geometric correspondence by means of the intersection of multiple partial solutions that are weighted through the MLESAC algorithm. The main advantage of our method is the extension of the algorithms based on the correspondence of invariant descriptors, generalizing the problem of correspondence to a geometric model in multiple views. In the sequences used we got an F-score = 97% at a distance of less than 1 pixel. These results show the effectiveness of the method and potentially can be used in a wide range of applications.

Original languageEnglish
Title of host publicationAdvances in Image and Video Technology - 5th Pacific Rim Symposium, PSIVT 2011, Proceedings
Pages192-203
Number of pages12
EditionPART 2
DOIs
StatePublished - 2011
Event5th Pacific-Rim Symposium on Video and Image Technology, PSIVT 2011 - Gwangju, Korea, Republic of
Duration: 20 Nov 201123 Nov 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume7088 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th Pacific-Rim Symposium on Video and Image Technology, PSIVT 2011
Country/TerritoryKorea, Republic of
CityGwangju
Period20/11/1123/11/11

Keywords

  • computer vision
  • correspondence problem
  • multiple view geometry
  • tracking

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