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

Zhenyu Liu; Runnan Fu; Linjun Wang; Yuzhen Jin; Theodoros Papakostas; Xenia Una Mainelli; Robert Voûte; Edward Verbree

doi:10.34726/1786

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

Zhenyu Liu, Runnan Fu, Linjun Wang, Yuzhen Jin, Theodoros Papakostas, Xenia Una Mainelli, Robert Voûte, Edward Verbree

GIS Technologie

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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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.

Original language	English
Title of host publication	LBS 2021: Proceedings of the 16th International Conference on Location Based Services
Editors	Anahid Basiri, Georg Gartner Gartner, Haosheng Huang
Publisher	TU Wien
Pages	183-194
Number of pages	12
DOIs	https://doi.org/10.34726/1786
Publication status	Published - 2021
Event	LBS 2021: 16th International Conference on Location Based Services (Online) - Glasgow, United Kingdom Duration: 24 Nov 2021 → 25 Nov 2021

Conference

Conference	LBS 2021: 16th International Conference on Location Based Services (Online)
Country/Territory	United Kingdom
City	Glasgow
Period	24/11/21 → 25/11/21

Keywords

Game Engine
Unreal Engine 4
3D Visualization
Situation Awareness
Point Cloud
Indoor Environment
Crisis Scenario

Access to Document

10.34726/1786

Game_Engine-based_Point_Cloud_Visualization_Perception(1)Final published version, 1.76 MBLicence: CC BY

Cite this

Liu, Z., Fu, R., Wang, L., Jin, Y., Papakostas, T., Mainelli, X. U., Voûte, R., & Verbree, E. (2021). Game Engine-based Point Cloud Visualization and Perception for Situation Awareness of Crisis Indoor Environments. In A. Basiri, G. G. Gartner, & H. Huang (Eds.), LBS 2021: Proceedings of the 16th International Conference on Location Based Services (pp. 183-194). TU Wien. https://doi.org/10.34726/1786

@inproceedings{0bc0b71f3b1c442bbc35fc92397c3aee,

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

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.",

keywords = "Game Engine, Unreal Engine 4, 3D Visualization, Situation Awareness, Point Cloud, Indoor Environment, Crisis Scenario",

author = "Zhenyu Liu and Runnan Fu and Linjun Wang and Yuzhen Jin and Theodoros Papakostas and Mainelli, {Xenia Una} and Robert Vo{\^u}te and Edward Verbree",

year = "2021",

doi = "10.34726/1786",

language = "English",

pages = "183--194",

editor = "Basiri, {Anahid } and Gartner, {Georg Gartner} and Huang, {Haosheng }",

booktitle = "LBS 2021: Proceedings of the 16th International Conference on Location Based Services",

publisher = "TU Wien",

note = "LBS 2021: 16th International Conference on Location Based Services (Online) ; Conference date: 24-11-2021 Through 25-11-2021",

}

Liu, Z, Fu, R, Wang, L, Jin, Y, Papakostas, T, Mainelli, XU, Voûte, R & Verbree, E 2021, Game Engine-based Point Cloud Visualization and Perception for Situation Awareness of Crisis Indoor Environments. in A Basiri, GG Gartner & H Huang (eds), LBS 2021: Proceedings of the 16th International Conference on Location Based Services. TU Wien, pp. 183-194, LBS 2021: 16th International Conference on Location Based Services (Online), Glasgow, United Kingdom, 24/11/21. https://doi.org/10.34726/1786

Game Engine-based Point Cloud Visualization and Perception for Situation Awareness of Crisis Indoor Environments. / Liu, Zhenyu; Fu, Runnan; Wang, Linjun et al.
LBS 2021: Proceedings of the 16th International Conference on Location Based Services. ed. / Anahid Basiri; Georg Gartner Gartner; Haosheng Huang. TU Wien, 2021. p. 183-194.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

TY - GEN

T1 - Game Engine-based Point Cloud Visualization and Perception for Situation Awareness of Crisis Indoor Environments

AU - Liu, Zhenyu

AU - Fu, Runnan

AU - Wang, Linjun

AU - Jin, Yuzhen

AU - Papakostas, Theodoros

AU - Mainelli, Xenia Una

AU - Voûte, Robert

AU - Verbree, Edward

PY - 2021

Y1 - 2021

N2 - 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.

AB - 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.

KW - Game Engine

KW - Unreal Engine 4

KW - 3D Visualization

KW - Situation Awareness

KW - Point Cloud

KW - Indoor Environment

KW - Crisis Scenario

U2 - 10.34726/1786

DO - 10.34726/1786

M3 - Conference contribution

SP - 183

EP - 194

BT - LBS 2021: Proceedings of the 16th International Conference on Location Based Services

A2 - Basiri, Anahid

A2 - Gartner, Georg Gartner

A2 - Huang, Haosheng

PB - TU Wien

T2 - LBS 2021: 16th International Conference on Location Based Services (Online)

Y2 - 24 November 2021 through 25 November 2021

ER -

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

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Keywords

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