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GLEAM -- An Illumination Estimation Framework for Real-time Photorealistic Augmented Reality on Mobile Devices (demo)

Published: 12 June 2019 Publication History

Abstract

Mixed reality mobile platforms attempt to co-locate virtual scenes with physical environments, towards creating immersive user experiences. However, to create visual harmony between virtual and physical spaces, the virtual scene must be accurately illuminated with realistic lighting that matches the physical environment. To this end, we design GLEAM, a framework that provides robust illumination estimation in real-time by integrating physical light-probe estimation with current mobile AR systems. We present a demo implementation of GLEAM by means of an AR application that estimates environmental illumination and renders the scene with real-time illumination updates. We demonstrate the efficacy of GLEAM's estimation against a current commercial status quo solution, Apple's ARKit, with the same application.

Cited By

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  • (2023)Toward Scalable and Controllable AR ExperimentationProceedings of the 1st ACM Workshop on Mobile Immersive Computing, Networking, and Systems10.1145/3615452.3617941(237-246)Online publication date: 6-Oct-2023
  • (2023)Audio Augmented Reality OutdoorsProceedings of the 2023 ACM International Conference on Interactive Media Experiences10.1145/3573381.3597028(199-204)Online publication date: 12-Jun-2023
  • (2023)Multi-Camera Lighting Estimation for Photorealistic Front-Facing Mobile Augmented RealityProceedings of the 24th International Workshop on Mobile Computing Systems and Applications10.1145/3572864.3580337(68-73)Online publication date: 22-Feb-2023
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cover image ACM Conferences
MobiSys '19: Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services
June 2019
736 pages
ISBN:9781450366618
DOI:10.1145/3307334
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 June 2019

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Author Tags

  1. augmented reality
  2. geometry
  3. image processing
  4. image-based lighting
  5. light estimation
  6. light probe
  7. lighting models

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  • Demonstration

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MobiSys '19
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Overall Acceptance Rate 274 of 1,679 submissions, 16%

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Cited By

View all
  • (2023)Toward Scalable and Controllable AR ExperimentationProceedings of the 1st ACM Workshop on Mobile Immersive Computing, Networking, and Systems10.1145/3615452.3617941(237-246)Online publication date: 6-Oct-2023
  • (2023)Audio Augmented Reality OutdoorsProceedings of the 2023 ACM International Conference on Interactive Media Experiences10.1145/3573381.3597028(199-204)Online publication date: 12-Jun-2023
  • (2023)Multi-Camera Lighting Estimation for Photorealistic Front-Facing Mobile Augmented RealityProceedings of the 24th International Workshop on Mobile Computing Systems and Applications10.1145/3572864.3580337(68-73)Online publication date: 22-Feb-2023
  • (2023)Demystifying Mobile Extended Reality in Web Browsers: How Far Can We Go?Proceedings of the ACM Web Conference 202310.1145/3543507.3583329(2960-2969)Online publication date: 30-Apr-2023
  • (2022)LITARProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35502916:3(1-29)Online publication date: 7-Sep-2022
  • (2022)Privacy-preserving Reflection Rendering for Augmented RealityProceedings of the 30th ACM International Conference on Multimedia10.1145/3503161.3548386(2909-2918)Online publication date: 10-Oct-2022
  • (2021)XiheProceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services10.1145/3458864.3467886(28-40)Online publication date: 24-Jun-2021
  • (2020)PointAR: Efficient Lighting Estimation for Mobile Augmented RealityComputer Vision – ECCV 202010.1007/978-3-030-58592-1_40(678-693)Online publication date: 3-Nov-2020
  • (2019)ShareARProceedings of the 18th ACM Workshop on Hot Topics in Networks10.1145/3365609.3365867(109-116)Online publication date: 13-Nov-2019

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