FocalSelect: Improving Occluded Objects Acquisition with Heuristic Selection and Disambiguation in Virtual Reality

Area of Science:

• Human-Computer Interaction
• Virtual Reality Systems
• Computer Graphics

Background:

• Existing virtual reality (VR) object selection methods often rely on ray-casting, limiting compatibility with other input modalities like bare hands.
• Some VR selection techniques disrupt scene context or user perspective, complicating post-selection manipulation and interaction.
• There is a need for intuitive and versatile object selection techniques in VR that preserve spatial context.

Purpose of the Study:

• To introduce FocalSelect, a novel heuristic selection technique for virtual reality (VR).
• To enable 3D disambiguation for occluded or distant targets using head-hand coordination.
• To evaluate FocalSelect's adaptability across input modalities and its performance against existing methods.

Main Methods:

• FocalSelect utilizes head-hand coordination and scoring-based functions for 3D disambiguation.
• The technique defines the intended selection range within a small sector of the headset's viewing frustum.
• A density-aware adjustable occlusion plane is employed for efficient depth culling of objects.

Main Results:

• FocalSelect demonstrated enhanced selection performance in occluded and remote scenarios.
• The technique effectively preserves the spatial context of objects within the virtual environment.
• Adaptability across different input modalities was confirmed through experimental evaluation.

Conclusions:

• FocalSelect offers an effective solution for object selection in challenging virtual reality (VR) environments.
• Preservation of spatial context facilitates user understanding and subsequent scene manipulation.
• The technique shows promise for practical applications and further enhancements in VR interaction design.