Immersive Analysis of Multifield Point Clouds

Abstract. Point clouds are used to measure and assess building processes in areas such as architecture, engineering, and construction. Precise spatial measurements can inform about deviations from a baseline, and the increasing use of sensor data in the context of building information modeling leads to multiple scalar fields containing rich information of individual spatial points. We propose an immersive approach to investigate such multivariate point cloud data from scans of buildings. We compare a switching approach that provides an overview of individual scalar fields with a spotlight that provides local information about all fields simultaneously. Furthermore, locomotion is compared for such immersive analysis with teleportation and with an omnidirectional treadmill. Our results show a preference for free movement and a task-dependence of visualization approaches for the inspection of scalar fields.