Publikation: Mesh2SLAM in VR : A Fast Geometry-Based SLAM Framework for Rapid Prototyping in Virtual Reality Applications
Lade...
Dateien
Zu diesem Dokument gibt es keine Dateien.
Datum
2025
Herausgeber:innen
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
DOI (zitierfähiger Link)
Internationale Patentnummer
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Core Facility der Universität Konstanz
Titel in einer weiteren Sprache
Publikationstyp
Beitrag zu einem Konferenzband
Publikationsstatus
Published
Erschienen in
2025 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops : VWR 2025, proceedings, 8-12 March 2025, Saint-Malo, France. Piscataway, NJ: IEEE, 2025, S. 57-62. ISBN 979-8-3315-1484-6. Verfügbar unter: doi: 10.1109/vrw66409.2025.00021
Zusammenfassung
SLAM is a foundational technique with broad applications in robotics and AR/VR. SLAM simulations evaluate new concepts, but testing on resource-constrained devices, such as VR HMDs, faces challenges: high computational cost and restricted sensor data access. This work proposes a sparse framework using mesh geometry projections as features, which improves efficiency and circumvents direct sensor data access, advancing SLAM research as we demonstrate in VR and through numerical evaluation.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
Schlagwörter
slam, real-time, virtual reality, efficient, fast, prototype, sparse, localization and mapping, compute shader, gpu, opengl es, 3d mesh
Konferenz
IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), 8. März 2025 - 12. März 2025, Saint Malo, France
Rezension
undefined / . - undefined, undefined
Zitieren
ISO 690
PINHEIRO DE SOUSA, Carlos, Heiko HAMANN, Oliver DEUSSEN, 2025. Mesh2SLAM in VR : A Fast Geometry-Based SLAM Framework for Rapid Prototyping in Virtual Reality Applications. IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW). Saint Malo, France, 8. März 2025 - 12. März 2025. In: 2025 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops : VWR 2025, proceedings, 8-12 March 2025, Saint-Malo, France. Piscataway, NJ: IEEE, 2025, S. 57-62. ISBN 979-8-3315-1484-6. Verfügbar unter: doi: 10.1109/vrw66409.2025.00021BibTex
@inproceedings{PinheirodeSousa2025-03-08Mesh2-74168,
title={Mesh2SLAM in VR : A Fast Geometry-Based SLAM Framework for Rapid Prototyping in Virtual Reality Applications},
year={2025},
doi={10.1109/vrw66409.2025.00021},
isbn={979-8-3315-1484-6},
address={Piscataway, NJ},
publisher={IEEE},
booktitle={2025 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops : VWR 2025, proceedings, 8-12 March 2025, Saint-Malo, France},
pages={57--62},
author={Pinheiro de Sousa, Carlos and Hamann, Heiko and Deussen, Oliver}
}RDF
<rdf:RDF
xmlns:dcterms="http://purl.org/dc/terms/"
xmlns:dc="http://purl.org/dc/elements/1.1/"
xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
xmlns:bibo="http://purl.org/ontology/bibo/"
xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
xmlns:foaf="http://xmlns.com/foaf/0.1/"
xmlns:void="http://rdfs.org/ns/void#"
xmlns:xsd="http://www.w3.org/2001/XMLSchema#" >
<rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/74168">
<dcterms:issued>2025-03-08</dcterms:issued>
<bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/74168"/>
<dc:creator>Pinheiro de Sousa, Carlos</dc:creator>
<dc:creator>Hamann, Heiko</dc:creator>
<foaf:homepage rdf:resource="http://localhost:8080/"/>
<dc:contributor>Hamann, Heiko</dc:contributor>
<dc:language>eng</dc:language>
<dc:contributor>Pinheiro de Sousa, Carlos</dc:contributor>
<void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
<dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2025-07-30T08:09:34Z</dc:date>
<dcterms:title>Mesh2SLAM in VR : A Fast Geometry-Based SLAM Framework for Rapid Prototyping in Virtual Reality Applications</dcterms:title>
<dcterms:abstract>SLAM is a foundational technique with broad applications in robotics and AR/VR. SLAM simulations evaluate new concepts, but testing on resource-constrained devices, such as VR HMDs, faces challenges: high computational cost and restricted sensor data access. This work proposes a sparse framework using mesh geometry projections as features, which improves efficiency and circumvents direct sensor data access, advancing SLAM research as we demonstrate in VR and through numerical evaluation.</dcterms:abstract>
<dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2025-07-30T08:09:34Z</dcterms:available>
<dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
<dc:contributor>Deussen, Oliver</dc:contributor>
<dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
<dc:creator>Deussen, Oliver</dc:creator>
</rdf:Description>
</rdf:RDF>Interner Vermerk
xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter
Prüfungsdatum der Dissertation
Finanzierungsart
Kommentar zur Publikation
Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Ja