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DC poleHodnotaJazyk
dc.contributor.authorHeinemann, Mika Benjamin
dc.contributor.authorKernbauer, Thomas
dc.contributor.authorFleck, Philipp
dc.contributor.authorArth, Clemens
dc.contributor.editorSkala, Václav
dc.date.accessioned2024-07-31T18:16:18Z-
dc.date.available2024-07-31T18:16:18Z-
dc.date.issued2024
dc.identifier.citationWSCG 2024: full papers proceedings: 32. International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, p. 299-306.en
dc.identifier.issn2464–4625 (online)
dc.identifier.issn2464–4617 (print)
dc.identifier.urihttp://hdl.handle.net/11025/57403
dc.format8 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencyen
dc.rights© Václav Skala - UNION Agencyen
dc.subjectrozšířená realitacs
dc.subjectprostorová rozšířená realitacs
dc.subjectreflektorcs
dc.titleSpotlight Control for Real-Time Targetingen
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedOff-road heavy machinery such as snow groomers or excavators, often operate in low-light and hazardous envi ronments. In this work, we explore the development of an intelligent camera-spotlight system with automatic and manual control to illuminate points of interest, such as obstacles or individuals at risk. We implement a prototype as proof of concept and integrate our workflow using a standard lighting protocol and a single-board computer. The presented calibration of the camera and spotlight ensures high precision in the desired use cases. In addition to testing the prototype on a real snow groomer, we evaluated its performance in terms of accuracy and repeatability. Overall, we showcase the usability of a commercially available spotlight in the context of spatial augmented reality in heavy machinery applications.en
dc.subject.translatedaugmented realityen
dc.subject.translatedspatial augmented realityen
dc.subject.translatedspotlighten
dc.identifier.doihttps://doi.org/10.24132/10.24132/CSRN.3401.32
dc.type.statusPeer revieweden
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