IEEE Trans Vis Comput Graph - An Intrinsic Algorithm for Parallel Poisson Disk Sampling on Arbitrary Surfaces.

Tópicos

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Resumo

Poisson disk sampling plays an important role in a variety of visual computing, due to its useful statistical property in distribution and the absence of aliasing artifacts. While many effective techniques have been proposed to generate Poisson disk distribution in Euclidean space, relatively few work has been reported to the surface counterpart. This paper presents an intrinsic algorithm for parallel Poisson disk sampling on arbitrary surfaces. We propose a new technique for parallelizing the dart throwing. Rather than the conventional approaches that explicitly partition the spatial domain to generate the samples in parallel, our approach assigns each sample candidate a random and unique priority that is unbiased with regard to the distribution. Hence, multiple threads can process the candidates simultaneously and resolve conflicts by checking the given priority values. It is worth noting that our algorithm is accurate as the generated Poisson disks are uniformly and randomly distributed without bias. Our method is intrinsic in that all the computations are based on the intrinsic metric and are independent of the embedding space. This intrinsic feature allows us to generate Poisson disk distributions on arbitrary surfaces. Furthermore, by manipulating the spatially varying density function, we can obtain adaptive sampling easily.

Resumo Limpo

poisson disk sampl play import role varieti visual comput due use statist properti distribut absenc alias artifact mani effect techniqu propos generat poisson disk distribut euclidean space relat work report surfac counterpart paper present intrins algorithm parallel poisson disk sampl arbitrari surfac propos new techniqu parallel dart throw rather convent approach explicit partit spatial domain generat sampl parallel approach assign sampl candid random uniqu prioriti unbias regard distribut henc multipl thread can process candid simultan resolv conflict check given prioriti valu worth note algorithm accur generat poisson disk uniform random distribut without bias method intrins comput base intrins metric independ embed space intrins featur allow us generat poisson disk distribut arbitrari surfac furthermor manipul spatial vari densiti function can obtain adapt sampl easili

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