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Spatiotemporal Sampling of Dynamic Environment Sequences
October 2011 (vol. 17 no. 10)
pp. 1499-1509
Liang Wan, Tianjin University, Tianjin, City University of Hong Kong, Hong Kong, and The Chinese University of Hong Kong, Hong Kong
Shue-Kwan Mak, City University of Hong Kong, Hong Kong
Tien-Tsin Wong, Chinese University of Hong Kong, Hong Kong
Chi-Sing Leung, City University of Hong Kong, Hong Kong
Environment sampling is a popular technique for rendering scenes with distant environment illumination. However, the temporal consistency of animations synthesized under dynamic environment sequences has not been fully studied. This paper addresses this problem and proposes a novel method, namely spatiotemporal sampling, to fully exploit both the temporal and spatial coherence of environment sequences. Our method treats an environment sequence as a spatiotemporal volume and samples the sequence by stratifying the volume adaptively. For this purpose, we first present a new metric to measure the importance of each stratified volume. A stratification algorithm is then proposed to adaptively suppress the abrupt temporal and spatial changes in the generated sampling patterns. The proposed method is able to automatically adjust the number of samples for each environment frame and produce temporally coherent sampling patterns. Comparative experiments demonstrate the capability of our method to produce smooth and consistent animations under dynamic environment sequences.

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Index Terms:
Spatiotemporal sampling, dynamic environment sequences, temporal consistency, importance metric, adaptive volume stratification.
Citation:
Liang Wan, Shue-Kwan Mak, Tien-Tsin Wong, Chi-Sing Leung, "Spatiotemporal Sampling of Dynamic Environment Sequences," IEEE Transactions on Visualization and Computer Graphics, vol. 17, no. 10, pp. 1499-1509, Oct. 2011, doi:10.1109/TVCG.2011.31
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