Using Smartphone EXIF Data to Classify Lighting Conditions for Outdoor Augmented Reality

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dc.contributor.authorNikolov, Ivanen_US
dc.contributor.authorMircov, Flavius-Alexandruen_US
dc.contributor.authorVillumsen, Jacob Holmen_US
dc.contributor.authorLarsen, Mike Lienen_US
dc.contributor.authorMadsen, Clausen_US
dc.contributor.editorGünther, Tobiasen_US
dc.contributor.editorMontazeri, Zahraen_US
dc.date.accessioned2025-05-09T09:31:35Z
dc.date.available2025-05-09T09:31:35Z
dc.date.issued2025
dc.description.abstractCorrectly matching real-world environment lighting conditions is an important step in making Augmented Reality content better fit with surrounding real objects. It is also the first step in larger, more complex problems like object relighting, shadow estimation, surface shading, etc. Dynamic classification of lighting conditions thus needs to be robust and lightweight. In this paper, we investigate the suitability of using pure EXIF data for classifying outdoor lighting conditions in four broad categories using a variety of shallow machine learning models. We gather a dataset of images together with EXIF metadata to test different models and show the results from the best-performing one in a real-time Augmented Reality application on a smartphone.en_US
dc.description.sectionheadersPosters
dc.description.seriesinformationEurographics 2025 - Posters
dc.identifier.doi10.2312/egp.20251023
dc.identifier.isbn978-3-03868-269-1
dc.identifier.issn1017-4656
dc.identifier.pages2 pages
dc.identifier.urihttps://doi.org/10.2312/egp.20251023
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/egp20251023
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Computing methodologies → Computer graphics; Machine learning; Mixed / augmented reality
dc.subjectComputing methodologies → Computer graphics
dc.subjectMachine learning
dc.subjectMixed / augmented reality
dc.titleUsing Smartphone EXIF Data to Classify Lighting Conditions for Outdoor Augmented Realityen_US
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