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1. Sparse Sampling and Completion for Light Transport in VPL-based Rendering | |||
Yuchi Huo, Rui Wang, Xinguo Liu, Hujun Bao | |||
Computer Science and Technology 26 November 2015 | |||
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Abstract:The many-light formulation provides a general framework for rendering various illumination effects using hundreds of thousands of virtual point lights (VPLs). To efficiently gather the contributions of the VPLs, lightcuts and its extensions cluster the VPLs, which implicitly approximates the lighting matrix with some representative blocks similar to vector quantization. In this paper, we propose a new approximation method based on the previous lightcut method and a low-rank matrix factorization model. As many researchers pointed out, the lighting matrix is low rank, which implies that it can be completed from a small set of known entries.We first generate a conservative global light cut with bounded error and partition the lighting matrix into slices by the coordinate and normal of the surface points using the method of lightslice. Then we perform two passes of randomly sampling on each matrix slice. In the first pass, uniformly distributed random entries are sampled to coarsen the global light cut, further clustering the similar light for the spatially localized surface points of the slices. In the second pass, more entries are sampled according to the possibility distribution function estimated from the first sampling result. Then each matrix slice is factorized into a product of two smaller low-rank matrices constrained by the sampled entries, which delivers a completion of the lighting matrix. The factorized form provides an additional speedup for adding up the matrix columns which is more GPU friendly. Compared with the previous lightcut based methods, we approximate the lighting matrix with some signal specialized bases via factorization. The experimental results shows that we can achieve significant acceleration than the state of the art many-light methods. | |||
TO cite this article:Yuchi Huo, Rui Wang, Xinguo Liu, et al. Sparse Sampling and Completion for Light Transport in VPL-based Rendering[OL].[26 November 2015] http://en.paper.edu.cn/en_releasepaper/content/4663747 |
2. Adjacency Sampling: A Scalable Line Drawing Kernel with Artifact Reduced | |||
Tang Chen,Li Sheng | |||
Computer Science and Technology 17 January 2011 | |||
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Abstract:In this paper we exploit sampling topology information in image space directly for visibility of line drawing and silhouette extraction. We propose a new line drawing kernel that depends on image-space adjacency test between primitives in GPU without any preprocessing step or extra adjacent information prestored. By this kernel, our visibility test acquires high accuracy in wireframe rendering and performs fairly well also in sketch and stylized line drawing, and our silhouette extraction method extracts visible portion of silhouette edges in image-space with clear and regular outlook. Our methods can be easily implemented and be controlled. The experiments show the privileges of our method in line drawing. | |||
TO cite this article:Tang Chen,Li Sheng. Adjacency Sampling: A Scalable Line Drawing Kernel with Artifact Reduced[OL].[17 January 2011] http://en.paper.edu.cn/en_releasepaper/content/4406859 |
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