Exploiting the Potential of Image Based Crowd Rendering

Abstract

Per-joint impostors have been used to achieve high performance when rendering thousands of agents, while still allowing us to blend animation. This provides interactively animated crowds and reduces the memory footprint compared to classic impostors. In this poster we exploit the potential of per joint impostors to further increase both visual quality and performance. The CAVAST framework for crowd simulation and rendering has been used to quantitatively evaluate our improvements with the profiling tools that it provides. Since different applications will have different requirements in terms of performance vs. visual quality, we have extended CAVAST with a new user interface to ease this process.