DP-LENS：一种用于沉浸式3D分析中遮挡管理的密度感知多焦点透镜，带有拓扑驱动自动路由功能
DP-LENS: A Density-Aware Polyfocal Lens with Topology-Driven Auto-Routing for Occlusion Management in Immersive 3D Analytics
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中文总结 AI 辅助
该研究针对沉浸式3D分析中数据遮挡导致的高认知负荷问题，提出带拓扑驱动自动路由的DP-LENS系统，结合LLM语音交互，经用户验证可降低负荷、提升效率，为相关系统设计提供启示。
中文摘要 AI 辅助
沉浸式环境（如虚拟现实VR）为探索复杂3D数据集提供了独特途径，但这类数据常存在严重遮挡，探索时认知负荷较高。本文提出DP-LENS，这是一种密度感知的多焦点鱼眼透镜，配备拓扑驱动自动路由功能，通过几何变形和3D透视技术保留周边上下文，同时让用户以更低认知负荷探索3D数据。为实现免提宏导航，我们集成大语言模型LLM作为补充的基于语音的目标选择工具，用于启动自动路由算法。两项共34名参与者的用户研究验证了该系统的潜在优势：第一项研究（N=18）将手动DP-LENS与两个行业标准基线（即微缩世界和体积切片）在严重遮挡的3D数据集上对比，结果显示DP-LENS显著降低了认知负荷、缩短了完成时间并提升了用户偏好；第二项研究（N=16）将语音启动的拓扑驱动自动路由系统与全手动DP-LENS对比，结果显示自动路由系统提升了任务效率、进一步降低了认知负荷并获得更高用户偏好，此外自动路由还部分解除了探索效率与数据物理尺寸的关联，一定程度上减轻了身体疲劳。基于这些发现，我们提出设计启示，为未来3D视觉分析系统开发更具空间可扩展性和低疲劳的交互方式提供参考。
英文摘要
Immersive environments, e.g., virtual reality (VR), offer a unique approach to exploring complex 3D datasets, where data is often heavily occluded and exploration incurs a high cognitive load. We propose DP-LENS, a density-aware polyfocal fisheye lens equipped with topology-driven auto-routing. While preserving peripheral context through geometric deformation and 3D perspective techniques, it enables users to explore 3D data with a lower cognitive load. To facilitate hands-free macro-navigation, we integrate a Large Language Model (LLM) to serve as a supplementary voice-based target selection tool that initiates the auto-routing algorithm. Two user studies with 34 participants investigate the potential benefits of this system. Our first study (N=18) compared the manual DP-LENS against two industry-standard baselines (i.e., World-in-Miniature and volumetric slicing) in heavily occluded 3D datasets. The results show that DP-LENS significantly reduced cognitive load, decreased completion time, and improved user preference. The second study (N=16) compared the topology-driven auto-routing system (initiated via voice commands) with a fully manual DP-LENS. The results show that the auto-routing system improved task efficiency, further reduced cognitive load, and garnered higher user preference. Furthermore, the auto-routing partially decoupled exploration efficiency from the physical dimensions of the data and mitigated physical fatigue to some extent. Based on the findings, we proposed design implications to inform the development of more spatially scalable and low-fatigue interactions for future 3D visual analytics systems.
