Cobzas, DanaDriedger, AndreAnsorger, AnnelieseGalay, ChanceLafitte, Chanelle2020-07-022022-05-312022-05-312020https://hdl.handle.net/20.500.14078/1622Presented in absentia on April 27, 2020 at "Student Research Day" at MacEwan University in Edmonton, Alberta. (Conference cancelled)Original 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.1.02MBPDFenAll Rights Reservedaugmented reality applicationsartworkStudent Presentation