Design and evaluation of 3D selection techniques based on progressive refinement

  • Authors:
  • Felipe Bacim;Regis Kopper;Doug A. Bowman

  • Affiliations:
  • -;-;-

  • Venue:
  • International Journal of Human-Computer Studies
  • Year:
  • 2013

Quantified Score

Hi-index 0.00

Visualization

Abstract

Issues such as hand and tracker jitter negatively affect user performance with 3D selection techniques based on the ray-casting metaphor. This makes it difficult for users to select objects that have a small visible area, since small targets require high levels of precision. We introduce an approach to address this issue that uses progressive refinement of the set of selectable objects to reduce the required precision of the task. We present three exemplar techniques (sphere-casting refined by QUAD menu (SQUAD), discrete zoom, and continuous zoom) and derive a preliminary design space for progressive refinement from their characteristics. We explore the trade-offs between progressive refinement and immediate selection techniques in two studies: first comparing SQUAD to ray-casting; and second comparing the zooming techniques to ray-casting. In both studies, an analytical evaluation based on a distal pointing model and an empirical evaluation demonstrates that progressive refinement selection can provide significant benefits compared to immediate techniques. In the first study, SQUAD was much more accurate than ray-casting, and SQUAD was faster than ray-casting with small targets and less cluttered environments. The issue with SQUAD, however, is that it requires all selectable objects to be visually distinct. The zooming techniques address this issue by exploring other areas of the progressive refinement design space. They allow users to use the spatial relationships among objects as criteria for selection and to increase precision without requiring precision in pointing. The results of the second study show that while the zooming techniques were significantly slower than ray-casting, accuracy was much higher. Additionally, depending on the size of the target, users chose not to use zoom and, therefore, performed as fast as with ray-casting.