Point&Spawn：扩展现实中利用注视与手势的无空间参考空中物体实例化
Point&Spawn: Mid-Air Reference-Free Object Instantiation Using Gaze and Hand Gestures in Extended Reality
- KAIST（韩国科学技术院）
- Aarhus University（奥胡斯大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文针对XR中无空间参考的空中物体实例化问题，提出Point&Spawn分阶段手势控制流程，通过用户研究对比不同方向与深度设定技术，为XR实例化交互设计提供实证指导。
AI中文摘要：
扩展现实（XR）中的空中物体实例化要求用户在无空间参考（如平面或现有物体）的情况下指定三维位置。本文提出Point&Spawn，这是一种分阶段流程，通过连续手势流中的方向设定、深度设定和位置细化实现预实例化位置指定。我们在包含24名受试者的用户研究中评估了六种无控制器技术，这些技术结合了注视或非优势手（NDH）方向设定，以及光线相交、相对增益或拖拽保持深度设定，覆盖近、远实例化深度。相对增益与拖拽保持相比光线相交，实现了更快、更准确的实例化，更低的工作量，更高的可用性和更强的偏好。以肩部为参考的NDH光线提升了速度和粗略精度，而基于视点的注视光线减少了手部移动且最终精度相当。更远的实例化深度带来了更高的时间成本，以及光线相交下的注视和精度成本。这些发现为XR实例化中的方向与深度控制设计提供了实证指导。
英文摘要：
Mid-air object instantiation in XR requires users to specify a 3D position without spatial references, such as surfaces or existing objects. We present Point&Spawn, a staged pipeline for pre-instantiation position specification through Direction Setting, Depth Setting, and Position Refinement within a continuous gesture flow. We evaluated six controller-free techniques combining Gaze or Non-Dominant Hand (NDH) direction setting with Ray Intersection, Relative Gain, or Drag&Hold depth setting in a user study (N=24) across Near and Far spawn depths. Relative Gain and Drag&Hold yielded faster and more accurate spawning, lower workload, higher usability, and greater preference than Ray Intersection. The shoulder-referenced NDH ray improved speed and coarse accuracy, whereas the viewpoint-based Gaze ray reduced hand movement with comparable final accuracy. Farther spawn depth imposed greater temporal costs as well as Gaze and accuracy costs with Ray Intersection. These findings offer empirical guidance for designing direction and depth control in spawning in XR.
