3D missing point estimation using fuzzy support vector regression

Laser line scanner are becoming very popular very recently because there is no touching the surface to determine coordinates. However, there are some missing points because of some parts of objects are out of sight from the laser. Therefore, in this research we introduce an automatic method to estim...

Full description

Saved in:

Bibliographic Details
Main Authors:	Winaipanich S., Auephanwiriyakul S., Theera-Umpon N.
Format:	Conference or Workshop Item
Language:	English
Published:	2014
Online Access:	http://www.scopus.com/inward/record.url?eid=2-s2.0-77954922581&partnerID=40&md5=bc3cf7d4cdbb161c88705e7b8c3854e7 http://cmuir.cmu.ac.th/handle/6653943832/1502
Tags:	Add Tag No Tags, Be the first to tag this record!
Institution:	Chiang Mai University
Language:	English

id	th-cmuir.6653943832-1502
record_format	dspace
spelling	th-cmuir.6653943832-15022014-08-29T09:29:23Z 3D missing point estimation using fuzzy support vector regression Winaipanich S. Auephanwiriyakul S. Theera-Umpon N. Laser line scanner are becoming very popular very recently because there is no touching the surface to determine coordinates. However, there are some missing points because of some parts of objects are out of sight from the laser. Therefore, in this research we introduce an automatic method to estimate missing points in a Cartesian coordinate system using fuzzy support vector regression (FSVR). We also compare our result with the one from support vector regression (SVR). The results show that the FSVR is a suitable method in missing 3D coordinates estimation. 2014-08-29T09:29:23Z 2014-08-29T09:29:23Z 2010 Conference Paper 9.78975E+12 81197 http://www.scopus.com/inward/record.url?eid=2-s2.0-77954922581&partnerID=40&md5=bc3cf7d4cdbb161c88705e7b8c3854e7 http://cmuir.cmu.ac.th/handle/6653943832/1502 English
institution	Chiang Mai University
building	Chiang Mai University Library
country	Thailand
collection	CMU Intellectual Repository
language	English
description	Laser line scanner are becoming very popular very recently because there is no touching the surface to determine coordinates. However, there are some missing points because of some parts of objects are out of sight from the laser. Therefore, in this research we introduce an automatic method to estimate missing points in a Cartesian coordinate system using fuzzy support vector regression (FSVR). We also compare our result with the one from support vector regression (SVR). The results show that the FSVR is a suitable method in missing 3D coordinates estimation.
format	Conference or Workshop Item
author	Winaipanich S. Auephanwiriyakul S. Theera-Umpon N.
spellingShingle	Winaipanich S. Auephanwiriyakul S. Theera-Umpon N. 3D missing point estimation using fuzzy support vector regression
author_facet	Winaipanich S. Auephanwiriyakul S. Theera-Umpon N.
author_sort	Winaipanich S.
title	3D missing point estimation using fuzzy support vector regression
title_short	3D missing point estimation using fuzzy support vector regression
title_full	3D missing point estimation using fuzzy support vector regression
title_fullStr	3D missing point estimation using fuzzy support vector regression
title_full_unstemmed	3D missing point estimation using fuzzy support vector regression
title_sort	3d missing point estimation using fuzzy support vector regression
publishDate	2014
url	http://www.scopus.com/inward/record.url?eid=2-s2.0-77954922581&partnerID=40&md5=bc3cf7d4cdbb161c88705e7b8c3854e7 http://cmuir.cmu.ac.th/handle/6653943832/1502
_version_	1681419682496643072

3D missing point estimation using fuzzy support vector regression

Similar Items