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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Published in | International journal of intelligent systems Vol. 25; no. 11; pp. 1103 - 1120 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Hoboken
Wiley Subscription Services, Inc., A Wiley Company
01.11.2010
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Subjects | |
Online Access | Get full text |
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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. |
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Bibliography: | istex:FFCB112CFD13A8023B8A576DD8BAECEC738C65EB ArticleID:INT20441 ark:/67375/WNG-WG5SCBD9-Z ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 |
ISSN: | 0884-8173 1098-111X 1098-111X |
DOI: | 10.1002/int.20441 |