Tensor Clustering for Rendering Many-Light Animations
Milos Hasan, Edgar Velazquez-Armendariz, Fabio Pellacini, Kavita Bala
Proceedings of EGSR 2008 (EGSR 2008)
Abstract:
Rendering animations of scenes with deformable objects, camera motion, and
complex illumination, including indirect lighting and arbitrary shading, is a
long-standing challenge. Prior work has shown that complex lighting can be
accurately approximated by a large collection of point lights. In this
formulation, rendering of animation sequences becomes the problem of
efficiently shading many surface samples from many lights across several
frames. This paper presents a tensor formulation of the animated many-light
problem, where each element of the tensor expresses the contribution of one
light to one pixel in one frame. We sparsely sample rows and columns of the
tensor, and introduce a clustering algorithm to select a small number of
representative lights to efficiently approximate the animation. Our algorithm
achieves efficiency by reusing representatives across frames, while minimizing
temporal flicker. We demonstrate our algorithm in a variety of scenes that
include deformable objects, complex illumination and arbitrary shading and show
that a surprisingly small number of representative lights is sufficient for
high quality rendering. We believe out algorithm will find practical use in
applications that require fast previews of complex animation.
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Acknowledgments: National Science Foundation (NSF),
Intel Corporation, NVidia for equipment donations.