LaMAR: Benchmarking Localization and Mapping for Augmented Reality

Paul-Edouard Sarlin, Mihai Dusmanu, Johannes L Schönberger, Pablo Speciale, Lukas Gruber, Viktor Larsson, Ondrej Miksik, Marc Pollefeys

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingpeer-review

Abstract

Localization and mapping is the foundational technology for augmented reality (AR) that enables sharing and persistence of digital content in the real world. While significant progress has been made, researchers are still mostly driven by unrealistic benchmarks not representative of real-world AR scenarios. In particular, benchmarks are often based on small-scale datasets with low scene diversity, captured from stationary cameras, and lacking other sensor inputs like inertial, radio, or depth data. Furthermore, ground-truth (GT) accuracy is mostly insufficient to satisfy AR requirements. To close this gap, we introduce a new benchmark with a comprehensive capture and GT pipeline, which allow us to co-register realistic AR trajectories in diverse scenes and from heterogeneous devices at scale. To establish accurate GT, our pipeline robustly aligns the captured trajectories against laser scans in a fully automatic manner. Based on this pipeline, we publish a benchmark dataset of diverse and large-scale scenes recorded with head-mounted and hand-held AR devices. We extend several state-of-the-art methods to take advantage of the AR specific setup and evaluate them on our benchmark. Based on the results, we present novel insights on current research gaps to provide avenues for future work in the community.
Original languageEnglish
Title of host publicationComputer Vision – ECCV 2022
Subtitle of host publication7th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part VII
PublisherSpringer
Pages686-704
Number of pages19
ISBN (Electronic)978-3-031-20071-7
ISBN (Print)978-3-031-20070-0
DOIs
Publication statusPublished - 2022
Externally publishedYes
Event17th European Conference on Computer Vision, ECCV 2022 - Tel Aviv, Israel
Duration: 2022 Oct 232022 Oct 27

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume13667
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th European Conference on Computer Vision, ECCV 2022
Country/TerritoryIsrael
CityTel Aviv
Period2022/10/232022/10/27

Subject classification (UKÄ)

  • Computer Vision and Robotics (Autonomous Systems)

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