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Lipschitz Pruning: Hierarchical Simplification of Primitive‐Based SDFs.

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Title: Lipschitz Pruning: Hierarchical Simplification of Primitive‐Based SDFs.
Authors: Barbier, Wilhem1,2 (AUTHOR), Sanchez, Mathieu2 (AUTHOR), Paris, Axel2 (AUTHOR), Michel, Élie2 (AUTHOR), Lambert, Thibaud2 (AUTHOR), Boubekeur, Tamy2 (AUTHOR), Paulin, Mathias1 (AUTHOR), Thonat, Theo2 (AUTHOR)
Source: Computer Graphics Forum. May2025, Vol. 44 Issue 2, p1-12. 12p.
Subjects: Tree pruning, Graphics processing units, Ray tracing, Rendering (Computer graphics)
Abstract: Rendering tree‐based analytical Signed Distance Fields (SDFs) through sphere tracing often requires to evaluate many primitives per tracing step, for many steps per pixel of the end image. This cost quickly becomes prohibitive as the number of primitives that constitute the SDF grows. In this paper, we alleviate this cost by computing local pruned trees that are equivalent to the full tree within their region of space while being much faster to evaluate. We introduce an efficient hierarchical tree pruning method based on the Lipschitz property of SDFs, which is compatible with hard and smooth CSG operators. We propose a GPU implementation that enables real‐time sphere tracing of complex SDFs composed of thousands of primitives with dynamic animation. Our pruning technique provides significant speedups for SDF evaluation in general, which we demonstrate on sphere tracing tasks but could also lead to significant improvement for SDF discretization or polygonization. [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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PubType: Academic Journal
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  Data: Lipschitz Pruning: Hierarchical Simplification of Primitive‐Based SDFs.
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  Data: <searchLink fieldCode="JN" term="%22Computer+Graphics+Forum%22">Computer Graphics Forum</searchLink>. May2025, Vol. 44 Issue 2, p1-12. 12p.
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  Data: <searchLink fieldCode="DE" term="%22Tree+pruning%22">Tree pruning</searchLink><br /><searchLink fieldCode="DE" term="%22Graphics+processing+units%22">Graphics processing units</searchLink><br /><searchLink fieldCode="DE" term="%22Ray+tracing%22">Ray tracing</searchLink><br /><searchLink fieldCode="DE" term="%22Rendering+%28Computer+graphics%29%22">Rendering (Computer graphics)</searchLink>
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  Data: Rendering tree‐based analytical Signed Distance Fields (SDFs) through sphere tracing often requires to evaluate many primitives per tracing step, for many steps per pixel of the end image. This cost quickly becomes prohibitive as the number of primitives that constitute the SDF grows. In this paper, we alleviate this cost by computing local pruned trees that are equivalent to the full tree within their region of space while being much faster to evaluate. We introduce an efficient hierarchical tree pruning method based on the Lipschitz property of SDFs, which is compatible with hard and smooth CSG operators. We propose a GPU implementation that enables real‐time sphere tracing of complex SDFs composed of thousands of primitives with dynamic animation. Our pruning technique provides significant speedups for SDF evaluation in general, which we demonstrate on sphere tracing tasks but could also lead to significant improvement for SDF discretization or polygonization. [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.70057
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      – SubjectFull: Ray tracing
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              Text: May2025
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              Y: 2025
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