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Boundary Detection in Particle-based Fluids.

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Title: Boundary Detection in Particle-based Fluids.
Authors: Sandim, Marcos1, Cedrim, Douglas1, Nonato, Luis Gustavo1, Pagliosa, Paulo2, Paiva, Afonso1
Source: Computer Graphics Forum. May2016, Vol. 35 Issue 2, p215-224. 10p. 11 Color Photographs, 1 Black and White Photograph, 1 Diagram, 2 Charts, 1 Graph.
Subjects: Computer graphics research, Computer art, Digital image processing, Computational geometry, Computer science
Abstract: This paper presents a novel method to detect free-surfaces on particle-based volume representation. In contrast to most particle-based free-surface detection methods, which perform the surface identification based on physical and geometrical properties derived from the underlying fluid flow simulation, the proposed approach only demands the spatial location of the particles to properly recognize surface particles, avoiding even the use of kernels. Boundary particles are identified through a Hidden Point Removal (HPR) operator used for visibility test. Our method is very simple, fast, easy to implement and robust to changes in the distribution of particles, even when facing large deformation of the free-surface. A set of comparisons against state-of-the-art boundary detection methods show the effectiveness of our approach. The good performance of our method is also attested in the context of fluid flow simulation involving free-surface, mainly when using level-sets for rendering purposes. [ABSTRACT FROM AUTHOR]
Copyright of Computer Graphics Forum is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: <searchLink fieldCode="JN" term="%22Computer+Graphics+Forum%22">Computer Graphics Forum</searchLink>. May2016, Vol. 35 Issue 2, p215-224. 10p. 11 Color Photographs, 1 Black and White Photograph, 1 Diagram, 2 Charts, 1 Graph.
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  Data: This paper presents a novel method to detect free-surfaces on particle-based volume representation. In contrast to most particle-based free-surface detection methods, which perform the surface identification based on physical and geometrical properties derived from the underlying fluid flow simulation, the proposed approach only demands the spatial location of the particles to properly recognize surface particles, avoiding even the use of kernels. Boundary particles are identified through a Hidden Point Removal (HPR) operator used for visibility test. Our method is very simple, fast, easy to implement and robust to changes in the distribution of particles, even when facing large deformation of the free-surface. A set of comparisons against state-of-the-art boundary detection methods show the effectiveness of our approach. The good performance of our method is also attested in the context of fluid flow simulation involving free-surface, mainly when using level-sets for rendering purposes. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Computer Graphics Forum is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1111/cgf.12824
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      – Code: eng
        Text: English
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      – SubjectFull: Digital image processing
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              M: 05
              Text: May2016
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