Gradient Field Estimation on Triangle Meshes

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dc.contributor.authorMancinelli, C.en_US
dc.contributor.authorLivesu, M.en_US
dc.contributor.authorPuppo, E.en_US
dc.contributor.editorLivesu, Marco and Pintore, Gianni and Signoroni, Albertoen_US
dc.date.accessioned2018-10-18T05:51:17Z
dc.date.available2018-10-18T05:51:17Z
dc.date.issued2018
dc.description.abstractThe estimation of the differential properties of a function sampled at the vertices of a discrete domain is at the basis of many applied sciences. In this paper, we focus on the computation of function gradients on triangle meshes. We study one face-based method (the standard the facto), plus three vertex based methods. Comparisons regard accuracy, ability to perform on different domain discretizations, and efficiency. We performed extensive tests and provide an in-depth analysis of our results. Besides some behaviour that is common to all methods, in our study we found that, considering both accuracy and efficiency, some methods are preferable to others. This directly translates to useful suggestions for the implementation of gradient estimators in research and industrial code.en_US
dc.description.sectionheadersGeometry Processing Toolkits
dc.description.seriesinformationSmart Tools and Apps for Graphics - Eurographics Italian Chapter Conference
dc.identifier.doi10.2312/stag.20181301
dc.identifier.isbn978-3-03868-075-8
dc.identifier.issn2617-4855
dc.identifier.pages87-96
dc.identifier.urihttps://doi.org/10.2312/stag.20181301
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/stag20181301
dc.publisherThe Eurographics Associationen_US
dc.subjectMathematics of computing
dc.subjectNumerical differentiation
dc.subjectComputing methodologies
dc.subjectMesh models
dc.subjectHuman
dc.subjectcentered computing
dc.subjectScientific visualization
dc.titleGradient Field Estimation on Triangle Meshesen_US
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