Perception-based model simplification for motion blur rendering

Motion blur effects are important to motion perception in visual arts, interactive games and animation applications. Usually, such motion blur rendering is quite time consuming, thus blocking the online/interactive use of the effects. Motivated by the human perception in relation to moving objects, this paper presents simplified geometric models that enable to speedup motion blur rendering, which has not been tracked in motion blur rendering specifically. We develop a novel algorithm to simplify models with motion-aware, to preserve the features whose characteristics are perceivable in motion. We deduce the formula to outline the level of detail simplification by the object moving velocity. Using our simplified models, methods for motion blur rendering can achieve the rendering quality as using the original models, and obtain the processing acceleration mostly. The experimental results have shown the effectiveness of our approach, more acceleration with the larger models or faster motion (e.g. for the dragon model with over a million facets, the motion-blur rendering via hierarchical stochastic rasterization is sped up by over 27 times).

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