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Title : DETECTION AND ROBUST ESTIMATION OF CYLINDER FEATURES IN POINT CLOUDS
Company : Purdue University
File Name : Su.pdf
Size : 414180
Type : application/pdf
Date : 20-Aug-2010
Downloads : 27

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Featured Paper by

Yun-Ting Su and James Bethel

The objective of this work is to develop new methods for efficient automatic 3D modeling of existing industrial installations from point cloud data. Traditionally, cylinder feature extraction algorithms utilize 5D Hough transforms, resulting in impractically high computational complexity. A more efficient approach uses a 2D Hough transform to estimate orientation followed by a 3D Hough transform to detect position, but still has extensive runtimes and lacks robustness in dense point cloud data.
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