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Processing three-dimensional laser s...

Vieira, Miguel.

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Processing three-dimensional laser scanner data for automotive styling design.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Processing three-dimensional laser scanner data for automotive styling design./
作者:	Vieira, Miguel.
面頁冊數:	115 p.
附註:	Source: Dissertation Abstracts International, Volume: 67-03, Section: B, page: 1674.
Contained By:	Dissertation Abstracts International67-03B.
標題:	Engineering, Mechanical. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3211193
ISBN:	9780542609237

Processing three-dimensional laser scanner data for automotive styling design.
Vieira, Miguel.

Processing three-dimensional laser scanner data for automotive styling design. - 115 p.

Source: Dissertation Abstracts International, Volume: 67-03, Section: B, page: 1674.

Thesis (Ph.D.)--Carnegie Mellon University, 2006.

This thesis describes novel methods for processing three-dimensional laser-scanner data for automotive styling design. We introduce methods for smoothing, surface fitting, and surface reconstruction, each one addressing distinct but associated problems with using scanned data for industrial design. Our smoothing operator removes geometric noise from the data over varying scales while preserving sharp edges and corners. Our surface fitting method automatically segments the scanned data into distinct regions approximated by parametric surface patches. Finally, our surface reconstruction method takes approximating surface patches and uses a spherical cover and an implicit partition of unity to create a piecewise-smooth reconstruction of the scanned points. All of our approaches take into consideration the strict engineering and aesthetic constraints of automotive design, and we demonstrate their effectiveness on real-world data.

ISBN: 9780542609237Subjects--Topical Terms:

783786
Engineering, Mechanical.

Processing three-dimensional laser scanner data for automotive styling design.
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520 $a This thesis describes novel methods for processing three-dimensional laser-scanner data for automotive styling design. We introduce methods for smoothing, surface fitting, and surface reconstruction, each one addressing distinct but associated problems with using scanned data for industrial design. Our smoothing operator removes geometric noise from the data over varying scales while preserving sharp edges and corners. Our surface fitting method automatically segments the scanned data into distinct regions approximated by parametric surface patches. Finally, our surface reconstruction method takes approximating surface patches and uses a spherical cover and an implicit partition of unity to create a piecewise-smooth reconstruction of the scanned points. All of our approaches take into consideration the strict engineering and aesthetic constraints of automotive design, and we demonstrate their effectiveness on real-world data.
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