Target assistance for object selection in mobile and head mounted augmented reality
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Date
2019
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University of New Brunswick
Abstract
Augmented reality (AR) – where a computing device (e.g., a mobile phone or a headmounted display) is used to view and interact with a virtual target displayed in the real world – is becoming more common. Selecting virtual targets is a main building block of interacting in AR, but it is particularly difficult because a user must also use the device to frame targets with the device’s camera in addition to selecting them. Further, targets in AR can have characteristics that make selecting them challenging, and which are not typically present in traditional interactive systems, including being occluded, outside of the view port, or moving. While assistance techniques – techniques that make pointing at and selecting digital objects easier – have been extensively studied in traditional digital mediums and pointing situations (e.g., pointing at icons on a desktop using a mouse), the novel challenges of AR make it unclear if my existing knowledge still applies.
Because target selection is particularly difficult and error prone in AR, I propose the use of three target assistance techniques from previous studies, which I apply in two new and untested AR device scenarios (i.e., for mobile devices and head-mounted displays). Targets in AR which are present in 3D world space were mapped to 2D screen space and then I applied the algorithmic target assistance for the mapped targets. Then I conducted two studies that compared my newly adapted target assistance techniques with standard selection techniques to assess their effectiveness in AR. My findings show that an adapted Bubble Cursor-based technique performs consistently best across five different target scenarios. My work provides new findings on how different assistance techniques perform under realistic target scenarios, demonstrating the promise of target assistance for augmented reality applications.