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Title:
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A 2-STAGE SAMPLE CULLING ALGORITHM FOR MOTION AND DEFOCUS BLUR RENDERING |
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Author(s):
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Yi-Jeng Wu, Der-Lor Way, Zen-Chung Shih |
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ISBN:
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978-989-8533-22-7 |
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Editors:
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Katherine Blashki and Yingcai Xiao |
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Year:
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2014 |
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Edition:
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Single |
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Keywords:
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Motion Blur, Defocus Blur, Stochastic Rasterization, Sample Test Efficiency (STE), Focal Depth |
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Type:
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Full Paper |
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First Page:
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173 |
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Last Page:
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180 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Motion blur and defocus blur are two common visual effects for rendering realistic camera images. This paper presents a novel clip space culling for stochastic rasterization to render motion and defocus blur. The proposed 2-stage process reduces the sample coverage using the clip space information at camera lens domain (UV) and time domain (T). First, a conventional range of the camera lens UV bound is obtained, and all samples outside this bound are culled. Second, a triangular equation formula is computed through each triangle vertex position in XYUVT space. Based on this equation, all samples outside the triangle are also culled. Our method achieves good sample test efficiency with low computation cost for the real-time stochastic rasterizer. Finally, the proposed method is demonstrated by means of various experiments and a comparison is made to previous works. |
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