Abstract
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.
Originalsprache | englisch |
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Seiten (von - bis) | 4730-4739 |
Seitenumfang | 10 |
Fachzeitschrift | IEEE Transactions on Visualization and Computer Graphics |
Jahrgang | 29 |
Ausgabenummer | 11 |
Frühes Online-Datum | 2 Okt. 2023 |
DOIs | |
Publikationsstatus | Veröffentlicht - 1 Nov. 2023 |
ASJC Scopus subject areas
- Software
- Signalverarbeitung
- Maschinelles Sehen und Mustererkennung
- Computergrafik und computergestütztes Design