Design and evaluation of a novel out-of-reach selection technique for VR using iterative refinement

• Tipo: Artigo em Revista Científica Internacional
• Data: 2017

Autores

Mendes, D (Autor) Outra; Medeiros, D (Autor) Outra; Sousa, M (Autor) Outra; Cordeiro, E (Autor) Outra; Ferreira, A (Autor) Outra; Jorge, JA (Autor) Outra

Revista

Título: Computers and Graphics

Vol. 67

Páginas: 95-102

ISSN: 0097-8493

Editora: Elsevier

Indexação

ISI Web of Knowledge - 22 Citações

Scopus - 37 Citações

Outras Informações

ID Authenticus: P-00N-2V4

DOI: 10.1016/j.cag.2017.06.003

Abstract (EN): 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 8