contributor author | Hao Song | |
contributor author | Hsi-Yung Feng | |
contributor author | Daoshan OuYang | |
date accessioned | 2017-05-09T00:27:17Z | |
date available | 2017-05-09T00:27:17Z | |
date copyright | June, 2008 | |
date issued | 2008 | |
identifier issn | 1530-9827 | |
identifier other | JCISB6-25988#021001_1.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/137613 | |
description abstract | A point cloud data set, a dense set of discrete coordinate points scanned or sampled from the surface of a 3D physical object or design model, is emerging as a new representation format for geometric modeling. This paper presents a new method to detect tangential discontinuities in point cloud data. The method introduces an original criterion, named as incompatibility, to quantify the magnitude of shape change in the vicinity of a data point. The introduced criterion is unique since in smooth regions of the underlying surface where shape change around a data point is small, the calculated incompatibilities tend to cluster around small values. At points close to tangential discontinuities, the calculated incompatibilities become relatively large. By modeling the incompatibilities of points in smooth regions following a statistical distribution, the proposed method identifies tangential discontinuities as those points whose incompatibilities are considered outliers with respect to the distribution. As the categorization of outliers is in effect independent of the underlying surface shape and sampling conditions of the data points, a threshold can be automatically determined via a generic procedure and used to identify tangential discontinuities. The effectiveness of the proposed method is demonstrated through many case studies using both simulated and practical point cloud data sets. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Automatic Detection of Tangential Discontinuities in Point Cloud Data | |
type | Journal Paper | |
journal volume | 8 | |
journal issue | 2 | |
journal title | Journal of Computing and Information Science in Engineering | |
identifier doi | 10.1115/1.2904930 | |
journal fristpage | 21001 | |
identifier eissn | 1530-9827 | |
keywords | Sampling (Acoustical engineering) | |
keywords | Noise (Sound) | |
keywords | Probability | |
keywords | Shapes | |
keywords | Errors AND Project tasks | |
tree | Journal of Computing and Information Science in Engineering:;2008:;volume( 008 ):;issue: 002 | |
contenttype | Fulltext | |