A parallel algorithm for improving the maximal property of Poisson disk sampling

Xiang, Ying; Li, Zhenhua; He, Ying

doi:10.1016/j.cad.2013.08.016

Cited by 10 publications

(5 citation statements)

References 31 publications

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“…Ying et al [15] propose a GPU-based approach that generates Poisson-disks on surfaces using the geodesic distance. The recent work of Ying et al [16] proposes a parallel approach to improve the maximal property of the Poisson disk sampling. The discrete exponential map is used for the surface sampling.…”

Section: Related Workmentioning

confidence: 99%

Efficient maximal Poisson-disk sampling and remeshing on surfaces

Guo

Yan

Jia

et al. 2015

Computers & Graphics

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Section: Related Workmentioning

confidence: 99%

Efficient maximal Poisson-disk sampling and remeshing on surfaces

Guo

Yan

Jia

et al. 2015

Computers & Graphics

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“…Yan [26] proposed an adaptive maximization algorithm based on gap processing. Based on method proposed by Ebeida, Ying [27] successfully proposed a new method that can be maximized on the GPU in parallel, significantly improving the efficiency of obtaining the maximum distribution of sampling points. Mitchell et al [28] provided a implemented algorithm for precise maximal Poisson-disk sampling in deterministic linear time.…”

Section: Research Status Of Poisson Disk Samplingmentioning

confidence: 99%

Boundary scenario generation method of the autonomous system based on adaptive Poisson disk sampling

Lu,

Wang,

Wang

2024

Preprint

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Generation of boundary scenario is a common approach used to test and evaluate the autonomous system. It can generate amount number of test cases in regions that demonstrate critical transitions in performance modes. However, getting sufficient test cases within boundaries in a short time remains a huge challenge for a system under test. The choice of sampling method has a great influence on efficiency and accuracy of the test. This paper proposed a new black-box test method based on adaptive Poisson disk sampling to search the test cases in decision boundary of system under test. Firstly, the idea of sequential sampling and optimization are borrowed to guide Poisson disk sampling to sample in the boundary region of the black-box system. In order to improve the convergence speed of the algorithm, an adaptive search strategy based on dichotomous method is adopted. In addition, an elimination criterion is proposed to further decrease the calculation cost and the introduction of invalid samples. Finally, two state-of-art methods were compared on nine different categories of benchmarks and two actual autonomous systems to demonstrate the validation and efficiency of proposed method. The result shows that the proposed method can obtain more information of the system with fewer samples.

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“…Euclidean distance is used in these approaches. Besides the Euclidean metric, the geodesic metric is also used for Poisson-disk sampling [38][39][40][41] . Surface sampling techniques can be also used for surface remeshing by computing the restricted Delaunay triangulation [42] .…”

Section: Poisson-disk Samplingmentioning

confidence: 99%

A Survey of Blue-Noise Sampling and Its Applications

Yan

Guo

Wang

et al. 2015

J. Comput. Sci. Technol.

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In this paper, we survey recent approaches to blue-noise sampling and discuss their beneficial applications. We discuss the sampling algorithms that use points as sampling primitives and classify the sampling algorithms based on various aspects, e.g., the sampling domain and the type of algorithm. We demonstrate several well-known applications that can be improved by recent blue-noise sampling techniques, as well as some new applications such as dynamic sampling and blue-noise remeshing.

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A parallel algorithm for improving the maximal property of Poisson disk sampling

Cited by 10 publications

References 31 publications

Efficient maximal Poisson-disk sampling and remeshing on surfaces

Efficient maximal Poisson-disk sampling and remeshing on surfaces

Boundary scenario generation method of the autonomous system based on adaptive Poisson disk sampling

A Survey of Blue-Noise Sampling and Its Applications

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