Immersive visualisation of point cloud data of railway environments

Resilient and reliable rail transport is an important key factor to combat climate change. To guarantee this, the state of the rail network needs to be monitored and tracked. A promising proxy data source to monitor the state of the rail infrastructure is point cloud data. Point cloud data requires significant computational and storage resources due to its intrinsic 3D nature, making it challenging to process and visualise. To face the visualisation challenge, immersive visualisation using head-mounted displays has been proposed. Benefits of immersive visualisation are the reduced time to insight, the intuitive user experience, and the possibility of collaborative viewing. Despite these benefits, immersive visualisation of point cloud data for the rail domain has not been explored yet. To bridge this gap, this work presents a working prototype to immersively visualise railway point cloud data. The prototype enables the user to load a point cloud scene and interact with the scene using natural hand gestures and voice commands. Manual interactions include scaling, rotating and translating the scene. Based on a small user evaluation, it was found that participants had difficulty with the voice commands to control the visibility of objects. Key focus points for a next iteration are dynamically loading large scenes with an adaptive level of detail and expanding hand gesture based interaction.