Occlusion-Free Conformal Lensing for Spatiotemporal Visualization in 3D Urban Analytics
Abstract
The visualization of temporal data on urban buildings, such as shadows, noise, and solar potential, plays a critical role in the analysis of dynamic urban phenomena. However, in dense and geographically constrained 3D urban environments, visual representations of time-varying building data often suffer from occlusion and visual clutter. To address these two challenges, we introduce an immersive lens visualization that integrates a view-dependent cutaway de-occlusion technique and a temporal display derived from a conformal mapping algorithm. The mapping process first partitions irregular building footprints into smaller, sufficiently regular subregions that serve as structural primitives. These subregions are then seamlessly recombined to form a conformal, layered layout for our temporal lens visualization. The view-responsive cutaway is inspired by traditional architectural illustrations, preserving the overall layout of the building and its surroundings to maintain users' sense of spatial orientation. This lens design enables the occlusion-free embedding of shape-adaptive temporal displays across building facades on demand, supporting rapid time-space association for the discovery, access and interpretation of spatiotemporal urban patterns. Guided by domain and design goals, we outline the rationale behind the lens visual and interaction design choices, such as the encoding of time progression and temporal values in the conforming lens image. A user study compares our approach against conventional juxtaposition and x-ray spatiotemporal designs. Results validate the usage and utility of our lens, showing that it improves task accuracy and completion time, reduces navigation effort, and increases user confidence. From these findings, we distill design recommendations and promising directions for future research on spatially-embedded lenses in 3D visualization and urban analytics.
Growth and citations
This paper is currently showing No growth state computed yet..
Citation metrics and growth state from academic sources (e.g. Semantic Scholar). See About for details.
Cited by (0)
No citing papers yet
Papers that cite this one will appear here once data is available.
View citations page →References (0)
No references in DB yet
References for this paper will appear here once ingested.
Related papers in Graphics
- See-through: Single-image Layer Decomposition for Anime Characters0 citations
- Point Vortex Dynamics on Closed Surfaces0 citations
- Pi-GS: Sparse-View Gaussian Splatting with Dense π^3 Initialization0 citations
Growth transitions
No transitions recorded yet
Growth state transitions will appear here once computed.