Multi-perspective occlusion-free urban navigation visualization

3D navigation, by virtue of its realism, provides rich, authentic, and visually immersive information that closely approximates the physical world, playing a crucial role in domains such as commerce and scientific research. However, current 3D navigation systems face challenges including the separation of multi-view information and the occlusion of navigation routes. This paper presents an occlusion-free, multi-perspective visualization method for urban navigation routes. We introduce an undulating curve surface and, through computation of an information detail metric, demonstrate that our surface enables rapid transitions from the focus to the context and supports visualization of much larger scene extents within the same screen space, compared to a monotonic cylindrical surface. We further enhance scene information delivery by segmenting the navigation route and adjusting the camera’s tilt angle and field of view to match different surface parameters. To eliminate occlusion of the navigation route, we adjust the position and scale of obstructing buildings, assigning distance-based weights. Compared to the fixed-weight approach, our distance-weighted approach highlights building position and shape features more effectively across varied scenarios. The proposed method is validated using an experimental scenario in a region of Barcelona. Experimental results indicate that our approach can effectively represent scenes at different scales while prominently displaying the navigation route, thereby enhancing the overall navigation experience.

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Publication Details

Journal
International Journal of Applied Earth Observation and Geoinformation
Published
2026-01-07
DOI
https://doi.org/10.1016/j.jag.2025.105074
Primary Topic
Computer Graphics and Visualization Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Multi-perspective occlusion-free urban navigation visualization

Junru Su, Shen Ying, Haoran Yang
International Journal of Applied Earth Observation and Geoinformation
Computer Graphics and Visualization Techniques
article

Multi-perspective occlusion-free urban navigation visualization

Junru Su, Shen Ying, Haoran Yang
article en

Abstract

3D navigation, by virtue of its realism, provides rich, authentic, and visually immersive information that closely approximates the physical world, playing a crucial role in domains such as commerce and scientific research. However, current 3D navigation systems face challenges including the separation of multi-view information and the occlusion of navigation routes. This paper presents an occlusion-free, multi-perspective visualization method for urban navigation routes. We introduce an undulating curve surface and, through computation of an information detail metric, demonstrate that our surface enables rapid transitions from the focus to the context and supports visualization of much larger scene extents within the same screen space, compared to a monotonic cylindrical surface. We further enhance scene information delivery by segmenting the navigation route and adjusting the camera’s tilt angle and field of view to match different surface parameters. To eliminate occlusion of the navigation route, we adjust the position and scale of obstructing buildings, assigning distance-based weights. Compared to the fixed-weight approach, our distance-weighted approach highlights building position and shape features more effectively across varied scenarios. The proposed method is validated using an experimental scenario in a region of Barcelona. Experimental results indicate that our approach can effectively represent scenes at different scales while prominently displaying the navigation route, thereby enhancing the overall navigation experience.

International Journal of Applied Earth Observation and GeoinformationVol. 146
Sustainable cities and communities
Openalex Percentile: Top 97%
Computer Graphics and Visualization Techniques
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Multi-perspective occlusion-free urban navigation visualization — Junru Su, Shen Ying, et al. · International Journal of Applied Earth Observation and Geoinformation (2026) | TGRS Research Map | TGRS