Game Engine-based Point Cloud Visualization and Perception for Situation Awareness of Crisis Indoor Environments

Conference Paper (2021)
Author(s)

Zhenyu Liu (Student TU Delft)

Runnan Fu (Student TU Delft)

Linjun Wang (Student TU Delft)

Yuzhen Jin (Student TU Delft)

Theodoros Papakostas (Student TU Delft)

Xenia Una Mainelli (Student TU Delft)

R. L. Voûte (CGI Nederland B.V, TU Delft - GIS Technologie)

E Verbree (TU Delft - GIS Technologie)

Research Group
GIS Technologie
Copyright
© 2021 Zhenyu Liu, Runnan Fu, Linjun Wang, Yuzhen Jin, Theodoros Papakostas, Xenia Una Mainelli, R.L. Voûte, E. Verbree
DOI related publication
https://doi.org/10.34726/1786
More Info
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Publication Year
2021
Language
English
Copyright
© 2021 Zhenyu Liu, Runnan Fu, Linjun Wang, Yuzhen Jin, Theodoros Papakostas, Xenia Una Mainelli, R.L. Voûte, E. Verbree
Research Group
GIS Technologie
Pages (from-to)
183-194
Reuse Rights

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Abstract

Because unknown interior layouts can have serious consequences in time-sensitive situations, crisis response teams request many potential solutions for visualizing indoor environments in crisis scenarios. This research uses a game engine to directly visualize point cloud data input of indoor environments for generating clear interaction between the environment and viewers, to aid decision-making in high-stress moments. The prospective final product is an integration of game-oriented visualization and cartography, hosted within Unreal Engine 4 (UE4), allowing users to navigate throughout an indoor environment, and customizing certain interaction features. The UE4 project consists of 4 modules: data preprocessing, render style, functional module, and user interface. Finally, this research uses a single-floor indoor point cloud dataset collected from a building in Rotterdam, the Netherlands for the implementation.