Design and evaluation of a novel out-of-reach selection technique for VR using iterative refinement. (October 2017)

• Record Type: Journal Article
• Authors: Mendes, Daniel; Medeiros, Daniel; Sousa, Maurício; Cordeiro, Eduardo; Ferreira, Alfredo; Jorge, Joaquim A.
• Is Part Of: Computers & graphics. Volume 67(2017)
• Page Start: 95
• Page End: 102
• Publication Date: 2017-10
• Subjects: 3D user interfaces -- Virtual reality -- Out-of-reach -- Object selection -- Progressive refinement; Computer graphics -- Periodicals; 006.6
• DOI: 10.1016/j.cag.2017.06.003
• Languages: English
• ISSNs: 0097-8493

Abstract

Highlights: A taxonomy to classify reach, cardinality and refinement on out-of-reach selections. We propose PRECIOUS, a novel out-of-reach selection technique. PRECIOUS employs an iterative progressive refinement strategy in Virtual Reality. User evaluation comparing PRECIOUS against state-of-the-art out-of-reach approaches. PRECIOUS is a versatile approach, combining accuracy with consistent selection times. Graphical abstract: Abstract: In interactive systems, the ability to select virtual objects is essential. In immersive virtual environments, object selection is usually done at arm's length in mid-air by directly intersecting the desired object with the user's hand. However, selecting objects outside user's arm-reach still poses significant challenges, which direct approaches fail to address. Techniques proposed to overcome such limitations often follow an arm-extension metaphor or favor selection volumes combined with ray-casting. Nonetheless, while these approaches work for room sized environments, they hardly scale up to larger scenarios with many objects. In this paper, we introduce a new taxonomy to classify existing selection techniques. In its wake, we propose PRECIOUS, a novel mid-air technique for selecting out-of-reach objects, featuring iterative refinement in Virtual Reality, an hitherto untried approach in this context. While comparable techniques have been developed for non-stereo and non-immersive environments, these are not suitable to Immersive Virtual Reality. Our technique is the first to employ an iterative progressive refinement in such settings. It uses cone-casting to select multiple objects and moves the user closer to them in each refinement step, to allow accurate selection of the desired target. A user evaluation showed that PRECIOUS compares favorably against state-of-the-art approaches. Indeed, our results indicate that PRECIOUS is a versatile approach to out-of-reach target acquisition, combining accurate selection with consistent task completion times across different scenarios.