ABSTRACT
It is generally accepted that Poisson disk sampling provides great properties in various applications in computer graphics. We present KD-tree based randomized tiling (KDRT), an efficient method to generate maximal Poisson-disk samples by replicating and conquering tiles clipped from a pattern of very small size. Our method is a two-step process: first, randomly clipping tiles from an MPS(Maximal Poisson-disk Sample) pattern, and second, conquering these tiles together to form the whole sample plane. The results showed that this method can efficiently generate maximal Poisson-disk samples with very small trade-off in bias error. There are two main contributions of this paper: First, a fast and robust Poisson-disk sample generation method is presented; Second, this method can be used to combine several groups of independently generated sample patterns to form a larger one, thus can be applied as a general parallelization scheme of any MPS methods.
- Michael Balzer, Thomas Schlömer, and Oliver Deussen. 2009. Capacity-constrained point distributions: a variant of Lloyd's method. Vol. 28. ACM. Google Scholar
Digital Library
- John Bowers, Rui Wang, Li-Yi Wei, and David Maletz. 2010. Parallel Poisson disk sampling with spectrum analysis on surfaces. In ACM Transactions on Graphics (TOG), Vol. 29. ACM, 166. Google Scholar
Digital Library
- Michael F Cohen, Jonathan Shade, Stefan Hiller, and Oliver Deussen. 2003. Wang tiles for image and texture generation. Vol. 22. ACM. Google Scholar
Digital Library
- Robert L Cook. 1986. Stochastic sampling in computer graphics. ACM Transactions on Graphics (TOG) 5, 1 (1986), 51--72. Google Scholar
Digital Library
- Fernando De Goes, Katherine Breeden, Victor Ostromoukhov, and Mathieu Desbrun. 2012. Blue noise through optimal transport. ACM Transactions on Graphics (TOG) 31, 6 (2012), 171. Google Scholar
Digital Library
- Mark AZ Dippé and Erling Henry Wold. 1985. Antialiasing through stochastic sampling. ACM Siggraph Computer Graphics 19, 3 (1985), 69--78. Google Scholar
Digital Library
- Fredo Durand. 2011. A frequency analysis of Monte-Carlo and other numerical integration schemes. (2011).Google Scholar
- Mohamed S Ebeida, Andrew A Davidson, Anjul Patney, Patrick M Knupp, Scott A Mitchell, and John D Owens. 2011. Efficient maximal Poisson-disk sampling. In ACM Transactions on Graphics (TOG), Vol. 30. ACM, 49. Google Scholar
Digital Library
- Mohamed S Ebeida, Scott A Mitchell, Muhammad A Awad, Chonhyon Park, Laura P Swiler, Dinesh Manocha, and Li-Yi Wei. 2014. Spoke darts for efficient high dimensional blue noise sampling. arXiv preprint arXiv:1408.1118 (2014).Google Scholar
- Mohamed S Ebeida, Scott A Mitchell, Anjul Patney, Andrew A Davidson, and John D Owens. 2012. A Simple Algorithm for Maximal Poisson-Disk Sampling in High Dimensions. In Computer Graphics Forum, Vol. 31. Wiley Online Library, 785--794. Google Scholar
Digital Library
- Manuel N Gamito and Steve C Maddock. 2009. Accurate multidimensional Poisson-disk sampling. ACM Transactions on Graphics (TOG) 29, 1 (2009), 8. Google Scholar
Digital Library
- Jianwei Guo, Dong-Ming Yan, Xiaohong Jia, and Xiaopeng Zhang. 2015. Efficient maximal Poisson-disk sampling and remeshing on surfaces. Computers & Graphics 46 (2015), 72--79. Google Scholar
Digital Library
- Cheuk Yiu Ip, M Adil Yalçin, David Luebke, and Amitabh Varshney. 2013. Pixelpie: Maximal poisson-disk sampling with rasterization. In Proceedings of the 5th High-Performance Graphics Conference. ACM, 17--26. Google Scholar
Digital Library
- Nima Khademi Kalantari and Pradeep Sen. 2012. Fast generation of approximate blue noise point sets. In Computer Graphics Forum, Vol. 31. Wiley Online Library, 1529--1535. Google Scholar
Digital Library
- Johannes Kopf, Daniel Cohen-Or, Oliver Deussen, and Dani Lischinski. 2006. Recursive Wang tiles for real-time blue noise. Vol. 25. ACM. Google Scholar
Digital Library
- Ares Lagae and Philip Dutré. 2005. A procedural object distribution function. ACM Transactions on Graphics (TOG) 24, 4 (2005), 1442--1461. Google Scholar
Digital Library
- Ares Lagae and Philip Dutré. 2008. A comparison of methods for generating Poisson disk distributions. In Computer Graphics Forum, Vol. 27. Wiley Online Library, 114--129.Google Scholar
- Matt Pharr, Wenzel Jakob, and Greg Humphreys. 2016. Physically based rendering: From theory to implementation. Morgan Kaufmann. Google Scholar
Digital Library
- Adrien Pilleboue, Gurprit Singh, David Coeurjolly, Michael Kazhdan, and Victor Ostromoukhov. 2015. Variance analysis for Monte Carlo integration. ACM Transactions on Graphics (TOG) 34, 4 (2015), 124. Google Scholar
Digital Library
- Thomas Schlmer and Oliver Deussen. 2011. Accurate Spectral Analysis of Two-Dimensional Point Sets. Journal of Graphics, GPU, and Game Tools 15, 3 (2011), 152--160.Google Scholar
Cross Ref
- Kartic Subr and Jan Kautz. 2013. Fourier analysis of stochastic sampling strategies for assessing bias and variance in integration. To appear in ACM TOG 32 (2013), 4. Google Scholar
Digital Library
- Florent Wachtel, Adrien Pilleboue, David Coeurjolly, Katherine Breeden, Gurprit Singh, Gaël Cathelin, Fernando de Goes, Mathieu Desbrun, and Victor Ostromoukhov. 2014. Fast Tile-based Adaptive Sampling with User-specified Fourier Spectra. ACM Trans. Graph. 33, 4, Article 56 (July 2014), 11 pages. Google Scholar
Digital Library
- Li-Yi Wei. 2008. Parallel Poisson disk sampling. In ACM Transactions on Graphics (TOG), Vol. 27. ACM, 20. Google Scholar
Digital Library
- Li-Yi Wei. 2010. Multi-class blue noise sampling. ACM Transactions on Graphics (TOG) 29, 4 (2010), 79. Google Scholar
Digital Library
- Yin Xu, Ligang Liu, Craig Gotsman, and Steven J Gortler. 2011. Capacity-constrained Delaunay triangulation for point distributions. Computers & Graphics 35, 3 (2011), 510--516. Google Scholar
Digital Library
- Dong-Ming Yan and Peter Wonka. 2013. Gap processing for adaptive maximal Poisson-disk sampling. ACM Transactions on Graphics (TOG) 32, 5 (2013), 148. Google Scholar
Digital Library
- Xiang Ying, Shi-Qing Xin, Qian Sun, and Ying He. 2013. An intrinsic algorithm for parallel poisson disk sampling on arbitrary surfaces. IEEE transactions on visualization and computer graphics 19, 9 (2013), 1425--1437. Google Scholar
Digital Library
- Cem Yuksel. 2015. Sample Elimination for Generating Poisson Disk Sample Sets. Comput. Graph. Forum 34, 2 (May 2015), 25--32. Google Scholar
Digital Library
Index Terms
Fast maximal Poisson-disk sampling by randomized tiling
Recommendations
Maximal poisson-disk sampling via sampling radius optimization
SA '16: SIGGRAPH ASIA 2016 PostersMaximal Poisson-disk Sampling (MPS) is a fundamental research topic in computer graphics. An ideal MPS pattern should satisfy three properties: bias-free, minimal distance, maximal coverage. The classic approach for generating MPS is dart throwing, but ...
Fast Poisson disk sampling in arbitrary dimensions
SIGGRAPH '07: ACM SIGGRAPH 2007 sketchesIn many applications in graphics, particularly rendering, generating samples from a blue noise distribution is important. However, existing efficient techniques do not easily generalize beyond two dimensions. Here I demonstrate a simple modification to ...
Fast Generation of Poisson-Disk Samples on Mesh Surfaces by Progressive Sample Projection
Generating well-distributed Poisson-disk samples with a blue noise power spectrum on 3D meshes is required by a wide range of applications in computer graphics. We introduce a novel method called Progressive Sample Projection that can generate massive ...




Comments