Perceptual evaluation of level of detail clothing for virtual humans

Abstract

Recent developments in crowd simulation have allowed thousands of characters to be rendered in real-time. Usually this is achieved through the use of Level of Detail (LOD) models for the individuals in the crowd. Perceptual studies have shown that image-based representations, i.e., impostors, can be used as imperceptible background substitutes for high-polygon models for skinned human characters, resulting in optimal rendering times and high visual fidelity. However, previous methods only showed humans dressed in clothes that were deformed using standard skinning methods. Highly deformable objects like cloth are not effectively depicted using these methods. Therefore, in this paper, we present the first perceptual evaluation of different LOD representations of humans wearing deformable (i.e., physically simulated) clothing. We show conclusively that impostors are startlingly effective at depicting the deformation properties of clothing and present useful guidelines for the development of crowd systems with thousands of realistically clothed humans.