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A Probabilistic Framework for Visual Localization in Ambiguous Scenes
Univrses AB, Stockholm, Sweden, SE-11826.ORCID iD: 0000-0001-7819-3541
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.ORCID iD: 0000-0001-8747-6359
Univrses AB, Stockholm, Sweden, SE-11826.
Univrses AB, Stockholm, Sweden, SE-11826.
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2023 (English)In: Proceedings - ICRA 2023: IEEE International Conference on Robotics and Automation, Institute of Electrical and Electronics Engineers (IEEE) , 2023, p. 3969-3975Conference paper, Published paper (Refereed)
Abstract [en]

Visual localization allows autonomous robots to relocalize when losing track of their pose by matching their current observation with past ones. However, ambiguous scenes pose a challenge for such systems, as repetitive structures can be viewed from many distinct, equally likely camera poses, which means it is not sufficient to produce a single best pose hypothesis. In this work, we propose a probabilistic framework that for a given image predicts the arbitrarily shaped posterior distribution of its camera pose. We do this via a novel formulation of camera pose regression using variational inference, which allows sampling from the predicted distribution. Our method outperforms existing methods on localization in ambiguous scenes. We open-source our approach and share our recorded data sequence at github.com/efreidun/vapor.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2023. p. 3969-3975
National Category
Computer Vision and Robotics (Autonomous Systems) Robotics Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-336775DOI: 10.1109/ICRA48891.2023.10160466ISI: 001036713003052Scopus ID: 2-s2.0-85168671933OAI: oai:DiVA.org:kth-336775DiVA, id: diva2:1798735
Conference
2023 IEEE International Conference on Robotics and Automation, ICRA 2023, London, United Kingdom of Great Britain and Northern Ireland, May 29 2023 - Jun 2 2023
Note

Part of ISBN 9798350323658

QC 20230920

Available from: 2023-09-20 Created: 2023-09-20 Last updated: 2024-03-12Bibliographically approved

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Zangeneh, FereidoonBruns, LeonardJensfelt, Patric

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