Optimizing image matches via a verification model

In the literature, we have seen a boom in wide‐baseline matching approaches proposed for locating correspondences between images. However, wrong correspondences or the so‐called outliers are still rather inevitable, especially in urban environments with the presence of repetitive structures, and/or...

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Bibliographic Details
Published inInternational journal of intelligent systems Vol. 25; no. 11; pp. 1103 - 1120
Main Authors Lee, Jimmy Addison, Yow, Kin-Choong
Format Journal Article
LanguageEnglish
Published Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.11.2010
Subjects
Cameras
Matching
Optimization
Real time
Seasons
Weather conditions
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Summary:In the literature, we have seen a boom in wide‐baseline matching approaches proposed for locating correspondences between images. However, wrong correspondences or the so‐called outliers are still rather inevitable, especially in urban environments with the presence of repetitive structures, and/or a large dissimilarity in viewpoints. In this paper, we propose a verification model to optimize the image matching results by significantly reducing the number of outliers. Several geometric and appearance‐based measurements are exploited, and conditional probability is used to compute the probability of each true correspondence. The model is validated by extensive experiments on images from the ZuBud database, which are taken in different weather conditions, seasons, and with different cameras. It is also demonstrated on a real‐time application of an image‐based navigation system. © 2010 Wiley Periodicals, Inc.
Bibliography:istex:FFCB112CFD13A8023B8A576DD8BAECEC738C65EB
ArticleID:INT20441
ark:/67375/WNG-WG5SCBD9-Z
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content type line 23
ISSN:0884-8173
1098-111X
1098-111X
DOI:10.1002/int.20441