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|a 10.1109/TVCG.2023.3320264
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|a eng
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|a Reyes-Aviles, Fernando
|e verfasserin
|4 aut
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|a Bag of World Anchors for Instant Large-Scale Localization
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|c 2023
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|a Date Revised 06.11.2023
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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| 520 |
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|a In this work, we present a novel scene description to perform large-scale localization using only geometric constraints. Our work extends compact world anchors with a search data structure to efficiently perform localization and pose estimation of mobile augmented reality devices across multiple platforms (e.g., HoloLens 2, iPad). The algorithm uses a bag-of-words approach to characterize distinct scenes (e.g., rooms). Since the individual scene representations rely on compact geometric (rather than appearance-based) features, the resulting search structure is very lightweight and fast, lending itself to deployment on mobile devices. We present a set of experiments demonstrating the accuracy, performance and scalability of our novel localization method. In addition, we describe several use cases demonstrating how efficient cross-platform localization facilitates sharing of augmented reality experiences
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|a Journal Article
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|a Fleck, Philipp
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|a Schmalstieg, Dieter
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|a Arth, Clemens
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|i Enthalten in
|t IEEE transactions on visualization and computer graphics
|d 1996
|g 29(2023), 11 vom: 02. Nov., Seite 4730-4739
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