IntenSelect+: Enhancing Score-Based Selection in Virtual Reality

Abstract

Object selection in virtual environments is one of the most common and recurring interaction tasks. Therefore, the used technique can critically influence the overall efficiency and usability of a system. IntenSelect is a scoring-based selection-by-volume technique that was shown to offer improved selection performance over conventional raycasting in virtual reality. This initial method, however, is most pronounced for small spherical objects that converge to a point-like appearance only, is hard to parameterize, and has inherent limitations in terms of flexibility. We present an enhanced version of IntenSelect called IntenSelect+ that was designed to overcome multiple shortcomings of the original IntenSelect approach. In an empirical within-subjects user study with 42 participants, we compared IntenSelect+ to IntenSelect and conventional raycasting on a variety of complex object configurations motivated by prior work. In addition to replicating the previously shown benefits of IntenSelect over raycasting, our results also demonstrate significant advantages of IntenSelect+ over IntenSelect regarding selection performance, task load, and user experience. We, therefore, conclude that IntenSelect+ is a promising enhancement of the original approach that enables faster, more precise, and more comfortable object selection in immersive virtual environments.

Publication
IEEE Transactions on Visualization and Computer Graphics, accepted for publication
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