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dc.contributor.author吳博舜en_US
dc.contributor.authorBo-Shun Wuen_US
dc.contributor.author荊宇泰en_US
dc.contributor.authorYu-Tai Chingen_US
dc.date.accessioned2014-12-12T02:27:53Z-
dc.date.available2014-12-12T02:27:53Z-
dc.date.issued2001en_US
dc.identifier.urihttp://140.113.39.130/cdrfb3/record/nctu/#NT900394083en_US
dc.identifier.urihttp://hdl.handle.net/11536/68610-
dc.description.abstract在醫學上,經由醫學影像所重建出來的模型通常具有非常多、不必要的多餘三角形,雖然現今的繪圖硬體能力比起以往已經有大幅度的改進了,但是仍然不足以應付如此龐大的資料,所以需要對模型作簡化來降低三角形數目。本篇論文提出了一個模型分類的簡化演算法,利用計算模型表面上頂點的曲率來作為我們分類的依據,我們利用邊線摺疊法來作為模型簡化的基礎,利用使用者分別對我們所分出來的各群指定的中止頂點數目來作為程式的終止條件。zh_TW
dc.description.abstractA geometric model obtained from volume data may contain huge number of vertices and triangles. We present a mesh simplification method based on vertices classification. Our algorithm calculates curvatures on vertices and uses a curvature-threshold parameter to classify the vertices into two sets. After classifying, we use two user-specified parameters to reduce the number of triangles to the specified number. The simplification algorithm is based on edge collapse operation.en_US
dc.language.isozh_TWen_US
dc.subject曲率zh_TW
dc.subject分類zh_TW
dc.subject簡化zh_TW
dc.subject邊線摺疊zh_TW
dc.subjectcurvatureen_US
dc.subjectclassifyen_US
dc.subjectsimplifyen_US
dc.subjectedge collapseen_US
dc.title在特徵保留網絡簡化上之研究zh_TW
dc.titleResearch on Feature Preserved Mesh Reductionen_US
dc.typeThesisen_US
dc.contributor.department資訊科學與工程研究所zh_TW
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