The effects of visual granularity on indoor spatial learning assisted by mobile 3D information displays

Abstract

There is growing interest in improving indoor navigation using 3D spatial visualizations rendered on mobile devices. However, the level of information conveyed by these visualization interfaces in order to best support indoor spatial learning has been poorly studied. This experiment investigates how learning of multi-level virtual buildings assisted by mobile 3D displays rendered at different levels of visual granularity effect subsequent unaided navigation tasks. The visual granularity levels include: a high fidelity model, low fidelity model, wireframe model and sparse model. Results showed that using the sparse model during learning led to the most accurate and efficient overall pointing and navigation performance and that between-floor judgments were less accurate when assistance during learning was unavailable. These findings demonstrate that more information is not necessarily better and provide new insights into the optimal information content to be included in mobile 3D visualization interfaces supporting indoor spatial learning and cognitive map development. © 2012 Springer-Verlag.