Liu, Z., Fu, R., Wang, L., Jin, Y., Papakostas, T., Mainelli, U., & Voûte, R. (2021). Game Engine-based Point Cloud Visualization and Perception for Situation Awareness of Crisis Indoor Environments. In A. Basiri, G. Gartner, & H. Huang (Eds.), LBS 2021: Proceedings of the 16th International Conference on Location Based Services (pp. 183–194). https://doi.org/10.34726/1786
Game Engine; unreal engine; 3D visualization; situation awareness; point cloud; crisis scenario
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.
Published in “Proceedings of the 16th International Conference on
Location Based Services (LBS 2021)”, edited by Anahid Basiri, Georg
Gartner and Haosheng Huang, LBS 2021, 24-25 November 2021,