Street-level visualization is an important application of 3D city models.Challenges to street-level visualization include the cluttering of buildings due to fine detail and visualization performance.In this paper,a novel method is proposed for streetlevel visualization based on visual saliency evaluation.The basic idea of the method is to preserve these salient buildings in a scene while removing those that are non-salient.The method can be divided into pre-processing procedures and real-time visualization.The first step in pre-processing is to convert 3D building models at higher Levels of Detail(Lo Ds) into LoD 1 models with simplified ground plans.Then,a number of index viewpoints are created along the streets; these indices refer to both the position and the direction of each street site.A visual saliency value is computed for each building,with respect to the index site,based on a visual difference between the original model and the generalized model.We calculate and evaluate three methods for visual saliency:local difference,global difference and minimum projection area.The real-time visualization process begins by mapping the observer to its closest indices.The street view is then generated based on the building information stored in those indexes.A user study shows that the local visual saliency method performs better than do the global visual saliency,area and image-based methods and that the framework proposed in this paper may improve the performance of 3D visualization.
