Design and evaluation of AMAZE: A multi-finger approach to select small and distant objects in dense virtual environments

Abstract

Object selection is vital in VR applications, as it allows users to interact with and manipulate virtual objects. In specialized contexts like molecular visualizations, VR objects may be small, distant, and situated in dense virtual environments, posing challenges such as reduced accuracy, increased error rates, and diminished user experience. This research explores the design and evaluation of a multi-finger continuous zoom-based technique for selecting targets that are small, distant and located in dense virtual environments. We design, evaluate and present two techniques, AMAZE and AMAZE-X via two studies. In our first study, we compared AMAZE to existing methods of Expand and Pinch-to-Select and found that it outperformed them in accurately selecting objects. AMAZE also ranked as the most natural and enjoyable technique. However, AMAZE had the highest task completion time, prompting us to refine it into AMAZE-X. We made two crucial adjustments: increasing the CD ratio and adding user-to-object distance visualization. We assessed AMAZE-X’s performance against the techniques from the first study. AMAZE-X demonstrated superior performance in terms of task completion time without errors, as well as being easy to use, learn, and the most favored technique among participants. Based on our findings, we offer four design recommendations for developing interaction techniques that cater to small, distant object selection in dense 3D virtual environments.