Perceptual Evaluation of Impostor Representations for Virtual Humans and Buildings

In large-scale simulations involving complex scenes, such as cities inhabited by crowds, simplifications are almost always necessary to achieve interactive frame-rates. Level of Detail (LOD) techniques such as reducing geometric complexity, or substituting impostor images for geometry, are usually employed. Image-based or impostor techniques have been gaining in popularity in recent years, along with hybrid methods that combine impostors and geometry, but perceptual issues with respect to such representations have been largely neglected to date. In this paper we evaluate the effectiveness of impostor representations for the real-time rendering and animation of static buildings and dynamic virtual humans. Using sets of psychophysical experiments, we establish some thresholds at which impostors are effective for static and dynamic objects, along with criteria for selecting transitions to geometry and update rates. We also compare the impact of two model representations (geometry and impostor), on the perception of human motion. We have found that impostors are an extremely effective substitute for detailed geometry in the target application area.