DP-LENS: A Density-Aware Polyfocal Lens with Topology-Driven Auto-Routing for Occlusion Management in Immersive 3D Analytics

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.