GazeRayCursor: Facilitating Virtual Reality Target Selection by Blending Gaze and Controller Raycasting

ABSTRACT
Raycasting is a common method for target selection in virtual reality (VR). However, it results in selection ambiguity whenever a ray intersects multiple targets that are located at different depths. To resolve these ambiguities, we estimate object depth by projecting the closest intersection between the gaze and controller rays onto the controller ray. An evaluation of this method found that it significantly outperformed a previous eye convergence depth estimation technique. Based on these results, we developed GazeRayCursor, a novel selection technique that enhances Raycasting, by leveraging gaze for object depth estimation. In a second study, we compared two variations of GazeRayCursor with RayCursor, a recent technique developed for a similar purpose, in a dense target environment. The results indicated that GazeRayCursor decreased selection time by 45.0% and reduced manual depth adjustments by a factor of 10 in a dense target environment. Our findings showed that GazeRayCursor is an effective method for target disambiguation in VR selection without incurring extra effort.

Di Laura Chen, Marcello Giordano, Hrvoje Benko, Tovi Grossman, and Stephanie Santosa. 2023. GazeRayCursor: Facilitating Virtual Reality Target Selection by Blending Gaze and Controller Raycasting. In 29th ACM Symposium on Virtual Reality Software and Technology (VRST 2023), October 9– 11, 2023, Christchurch, New Zealand. ACM, New York, NY, USA, 11 pages. [ Ссылка ]

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