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dc.contributor.authorGarro, Valeriaen_US
dc.contributor.authorPintore, Giovannien_US
dc.contributor.authorGanovelli, Fabioen_US
dc.contributor.authorGobbetti, Enricoen_US
dc.contributor.authorScopigno, Robertoen_US
dc.contributor.editorMatthias Hullin and Marc Stamminger and Tino Weinkaufen_US
dc.date.accessioned2016-10-10T08:04:06Z
dc.date.available2016-10-10T08:04:06Z
dc.date.issued2016
dc.identifier.isbn978-3-03868-025-3
dc.identifier.issn-
dc.identifier.urihttp://dx.doi.org/10.2312/vmv.20161339
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/vmv20161339
dc.description.abstractWe present a novel algorithm for fast metric reconstruction on mobile devices using a combination of image and inertial acceleration data. In contrast to previous approaches to this problem, our algorithm does not require a long acquisition time or intensive data processing and can be implemented entirely on common IMU-enabled tablet and smartphones. The method recovers real world units by comparing the acceleration values from the inertial sensors with the ones inferred from images. In order to cope with IMU signal noise, we propose a novel RANSAC-like strategy which helps to remove the outliers. We demonstrate the effectiveness and the accuracy of our method through an integrated mobile system returning point clouds in metric scale.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.4.8 [Computer Graphics]
dc.subjectImage processing and computer vision
dc.subjectScene analysis
dc.titleFast Metric Acquisition with Mobile Devicesen_US
dc.description.seriesinformationVision, Modeling & Visualization
dc.description.sectionheadersReconstructing and Understanding the World
dc.identifier.doi10.2312/vmv.20161339
dc.identifier.pages29-36


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  • VMV16
    ISBN 978-3-03868-025-3

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