КФУ. Карточка публикации. A comparison of Gaussian and mean curvature estimation methods on triangular meshes of range image data

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A COMPARISON OF GAUSSIAN AND MEAN CURVATURE ESTIMATION METHODS ON TRIANGULAR MESHES OF RANGE IMAGE DATA

Форма представления

Статьи в зарубежных журналах и сборниках

Год публикации

2007

Язык

английский

Авторы, сотрудники КФУ

Магид Евгений Аркадьевич, автор

Библиографическое описание на языке оригинала

Magid E. A comparison of Gaussian and mean curvature estimation methods on triangular meshes of range image data / Soldea O., & Rivlin E. Computer Vision and Image Understanding. - 2007. - Vol. 107(3). - p. 139-159.

Аннотация

Computer Vision and Image Understanding

Ключевые слова

Geometric modeling; Principal curvatures; Gaussian curvature; Mean curvature; Polygonal mesh; Triangular mesh; Range data

Название журнала

Computer Vision and Image Understanding

URL

https://www.sciencedirect.com/science/article/pii/S1077314206001585

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https://repository.kpfu.ru/?p_id=257651

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Полная запись метаданных

Поле DC	Значение	Язык
dc.contributor.author	Магид Евгений Аркадьевич	ru_RU
dc.date.accessioned	2007-01-01T00:00:00Z	ru_RU
dc.date.available	2007-01-01T00:00:00Z	ru_RU
dc.date.issued	2007	ru_RU
dc.identifier.citation	Magid E. A comparison of Gaussian and mean curvature estimation methods on triangular meshes of range image data / Soldea O., & Rivlin E. Computer Vision and Image Understanding. - 2007. - Vol. 107(3). - p. 139-159.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/?p_id=257651	ru_RU
dc.description.abstract	Computer Vision and Image Understanding	ru_RU
dc.description.abstract	Estimating intrinsic geometric properties of a surface from a polygonal mesh obtained from range data is an important stage of numerous algorithms in computer and robot vision, computer graphics, geometric modeling, and industrial and biomedical engineering. This work considers different computational schemes for local estimation of intrinsic curvature geometric properties. Four different algorithms and their modifications were tested on triangular meshes that represent tessellations of synthetic geometric models. The results were compared with the analytically computed values of the Gaussian and mean curvatures of the non-uniform rational B-spline (NURBS) surfaces from which these meshes originated. The algorithms were also tested on range images of geometric objects. The results were compared with the analytic values of the Gaussian and mean curvatures of the scanned geometric objects. This work manifests the best algorithms suited for Gaussian and mean curvature estimation, and shows that different algorithms should be employed to compute the Gaussian and mean curvatures.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject		ru_RU
dc.title	A comparison of Gaussian and mean curvature estimation methods on triangular meshes of range image data	ru_RU
dc.type	Статьи в зарубежных журналах и сборниках	ru_RU