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...
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2014
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| 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 |
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| Institution: | Chiang Mai University |
| Language: | English |
| Summary: | 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. |
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