Epiflow based stereo fusion

Hongsheng Zhang, Shahriar Negahdaripour

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

3-D reconstruction from images sequences has been the center topic of computer vision. Real-time applications call for causal processing of stereo sequences, as they are acquired, covering different regions of the scene. The first step is to compute the current stereo disparity, and recursive map building often requires fusing with the previous estimate. In this paper, the epiflow framework [1], originally proposed for establishing matches among stereo feature pairs is generalized to devise an iterative causal algorithm for stereo disparity map fusion. In the context of disparity fusion, quadruplet correspondence of the epiflow tracking algorithm becomes reminiscent of the "closest point" of the 3-D ICP algorithm. Unlike ICP, the 2-D epiflow framework permits incorporating both photometric and geometrical constraints, estimation of the stereo rig motion as supplementary information, as well as identifying local inconsistencies between the two disparity maps. Experiments with real data validate the proposed approach, and improved converge compared to the ICP algorithm.

Original languageEnglish (US)
Title of host publicationPattern Recognition and Image Analysis - Third Iberian Conference, IbPRIA 2007, Proceedings
Pages153-160
Number of pages8
EditionPART 1
StatePublished - Dec 1 2007
Event3rd Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2007 - Girona, Spain
Duration: Jun 6 2007Jun 8 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume4477 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other3rd Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2007
CountrySpain
CityGirona
Period6/6/076/8/07

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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