Rendering of feature-rich dynamically changing volumetric datasets on GPU

Interactive photo-realistic representation of dynamic liquid volumes is a challenging task for today's GPUs and state-of-the-art visualization algorithms. Methods of the last two decades consider either static volumetric datasets applying several optimizations for volume casting, or dynamic volumetric datasets with rough approximations to realistic rendering. Nevertheless, accurate real-time visualization of dynamic datasets is crucial in areas of scientific visualization as well as areas demanding for accurate rendering of feature-rich datasets. An accurate and thus realistic visualization of such datasets leads to new challenges: due to restrictions given by computational performance, the datasets may be relatively small compared to the screen resolution, and thus each voxel has to be rendered highly oversampled. With our volumetric datasets based on a real-time lattice Boltzmann fluid simulation creating dynamic cavities and small droplets, existing real-time implementations are not applicable for a realistic surface extraction. This work presents a volume tracing algorithm capable of producing multiple refractions which is also robust to small droplets and cavities. Furthermore we show advantages of our volume tracing algorithm compared to other implementations.