We present a new method for procedurally generating window lighting and building interior effects for real-time rendering of city scenes. Our method can selectively light a random subset of windows on the building with varying color and brightness. This window light can be combined with cube maps of representative building interior (i.e. interior maps) to generate rich details at different scales in large-scale city rendering. Our method relies solely on window transparency cutout (alpha) layer and a simple texture parameterization scheme in the building models and requires no additional information to be stored per building. The algorithm can be implemented completely in a fragment shader function, which makes it suitable for integration into existing render engines. The percentage of window lighting can be adjusted smoothly using a single parameter. We demonstrate our method using a large-scale 3D city data set, running with interactive frame rates on both PC and mobile platforms.

Particle tracing in time-varying flow fields is traditionally performed by numerical integration of the underlying vector field. This procedure can become computationally expensive, especially in scattered, particle-based flow fields, which complicate interpolation due to the lack of an explicit neighborhood structure. If such a particle-based flow field allows for the identification of consecutive particle positions, an alternative approach to particle tracing can be employed: we substitute repeated numerical integration of vector data by geometric interpolation in the highly dynamic particle system as defined by the particle-based simulation. To allow for efficient and accurate location and interpolation of changing particle neighborhoods, we develop a modified k-d tree representation that is capable of creating a dynamic partitioning of even highly compressible data sets with strongly varying particle densities. With this representation we are able to efficiently perform pathline computation by identifying, tracking, and updating an enclosing, dynamic particle neighborhood as particles move overtime. We investigate and evaluate the complexity, accuracy, and robustness of this interpolation-based alternative approach to trajectory generation in compressible and incompressible particle systems generated by simulation techniques such as Smoothed Particle Hydrodynamics (SPH).