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496 Capstone: AR.t

dc.contributor.advisorCobzas, Dana
dc.contributor.authorDriedger, Andre
dc.contributor.authorAnsorger, Anneliese
dc.contributor.authorGalay, Chance
dc.contributor.authorLafitte, Chanelle
dc.date.accessioned2020-07-02
dc.date.accessioned2022-05-31T01:15:00Z
dc.date.available2022-05-31T01:15:00Z
dc.date.issued2020
dc.descriptionPresented in absentia on April 27, 2020 at "Student Research Day" at MacEwan University in Edmonton, Alberta. (Conference cancelled)
dc.description.abstractOriginal artwork is often very expensive; being able to see how a painting will look on a wall before you buy is advantageous. As a collaborative project between the MacEwan Computer Science and Design departments, we set out to do develop an AR app that can be used by by consumers to shop for art on the walls of their homes and offices. Existing mobile AR applications cannot identify vertical surfaces, such as walls. Our solution is to implement a target image that can be posted onto vertical surfaces to be detected by our app. We developed an OpenCV prototype to test this method of using object-detection to set a starting point for subsequent tracking. The prototype was successful in rendering 3d objects, true to scale, onto walls. Next, we developed an Android version utilizing Google's ARCore toolkit. This also delivered good results. Ultimately, we were successful in showcasing art on walls using smartphones in real-time.
dc.format.extent1.02MB
dc.format.mimetypePDF
dc.identifier.urihttps://hdl.handle.net/20.500.14078/1622
dc.languageEnglish
dc.language.isoen
dc.relation.urihttps://roam.macewan.ca/islandora/object/gm:2149
dc.relation.urihttps://roam.macewan.ca/islandora/object/gm:2150
dc.relation.urihttps://roam.macewan.ca/islandora/object/gm:2151
dc.rightsAll Rights Reserved
dc.subjectaugmented reality applications
dc.subjectartwork
dc.title496 Capstone: AR.ten
dc.typeStudent Presentation
dspace.entity.type

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