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Image alignment for panorama stitching in sparsely structured environments
Linköping University, Faculty of Science & Engineering. Linköping University, Department of Electrical Engineering, Computer Vision.
Linköping University, Faculty of Science & Engineering. Linköping University, Department of Electrical Engineering, Computer Vision.
Linköping University, Faculty of Science & Engineering. Linköping University, Department of Electrical Engineering, Computer Vision.ORCID iD: 0000-0002-6096-3648
Linköping University, Faculty of Science & Engineering. Linköping University, Department of Electrical Engineering, Computer Vision.
2015 (English)Conference paper (Refereed)
Abstract [en]

Panorama stitching of sparsely structured scenes is an open research problem. In this setting, feature-based image alignment methods often fail due to shortage of distinct image features. Instead, direct image alignment methods, such as those based on phase correlation, can be applied. In this paper we investigate correlation-based image alignment techniques for panorama stitching of sparsely structured scenes. We propose a novel image alignment approach based on discriminative correlation filters (DCF), which has recently been successfully applied to visual tracking. Two versions of the proposed DCF-based approach are evaluated on two real and one synthetic panorama dataset of sparsely structured indoor environments. All three datasets consist of images taken on a tripod rotating 360 degrees around the vertical axis through the optical center. We show that the proposed DCF-based methods outperform phase correlation-based approaches on these datasets.

Place, publisher, year, edition, pages
2015.
Series
Lecture Notes in Computer Science, ISSN 0302-9743 (print), 1611-3349 (online)
Keyword [en]
Image alignment, Panorama stitching, Image registration, Phase correlation, Discriminative correlation filters
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-121566DOI: 10.1007/978-3-319-19665-7_36ISBN: 978-3-319-19664-0ISBN: 978-3-319-19665-7OAI: oai:DiVA.org:liu-121566DiVA: diva2:856868
Conference
19th Scandinavian Conference, SCIA 2015, Copenhagen, Denmark, June 15-17, 2015
Projects
VPS
Available from: 2015-09-25 Created: 2015-09-25 Last updated: 2016-06-02

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Meneghetti, GiuliaDanelljan, MartinFelsberg, MichaelNordberg, Klas
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Computer Vision and Robotics (Autonomous Systems)

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ReferencesLink to record
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