3D Object Recognition Using Multiple Views And Neural Networks.
This paper proposes a method for recognition and classification of 3D objects. The method is based on 2D moments and neural networks. The 2D moments are calculated based on 2D intensity images taken from multiple cameras that have been arranged using multiple views technique. 2D moments are commonly...
| Main Authors: | , , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2006
|
| Subjects: | |
| Online Access: | http://eprints.usm.my/14448/ http://eprints.usm.my/14448/1/paper2.pdf |
| _version_ | 1848872033957445632 |
|---|---|
| author | Mashor, M Y Osman, M K Arshad, M R |
| author_facet | Mashor, M Y Osman, M K Arshad, M R |
| author_sort | Mashor, M Y |
| building | USM Institutional Repository |
| collection | Online Access |
| description | This paper proposes a method for recognition and classification of 3D objects. The method is based on 2D moments and neural networks. The 2D moments are calculated based on 2D intensity images taken from multiple cameras that have been arranged using multiple views technique. 2D moments are commonly used for 2D pattern recognition.
|
| first_indexed | 2025-11-15T15:49:33Z |
| format | Conference or Workshop Item |
| id | usm-14448 |
| institution | Universiti Sains Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T15:49:33Z |
| publishDate | 2006 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | usm-144482017-11-20T07:22:08Z http://eprints.usm.my/14448/ 3D Object Recognition Using Multiple Views And Neural Networks. Mashor, M Y Osman, M K Arshad, M R TK1-9971 Electrical engineering. Electronics. Nuclear engineering This paper proposes a method for recognition and classification of 3D objects. The method is based on 2D moments and neural networks. The 2D moments are calculated based on 2D intensity images taken from multiple cameras that have been arranged using multiple views technique. 2D moments are commonly used for 2D pattern recognition. 2006 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.usm.my/14448/1/paper2.pdf Mashor, M Y and Osman, M K and Arshad, M R (2006) 3D Object Recognition Using Multiple Views And Neural Networks. In: International Conference on Man-Machine Systems (ICoMMS 2006), 15-16 September 2006, City Bayview Hotel, Langkawi, Malaysia. |
| spellingShingle | TK1-9971 Electrical engineering. Electronics. Nuclear engineering Mashor, M Y Osman, M K Arshad, M R 3D Object Recognition Using Multiple Views And Neural Networks. |
| title | 3D Object Recognition Using Multiple Views And Neural Networks. |
| title_full | 3D Object Recognition Using Multiple Views And Neural Networks. |
| title_fullStr | 3D Object Recognition Using Multiple Views And Neural Networks. |
| title_full_unstemmed | 3D Object Recognition Using Multiple Views And Neural Networks. |
| title_short | 3D Object Recognition Using Multiple Views And Neural Networks. |
| title_sort | 3d object recognition using multiple views and neural networks. |
| topic | TK1-9971 Electrical engineering. Electronics. Nuclear engineering |
| url | http://eprints.usm.my/14448/ http://eprints.usm.my/14448/1/paper2.pdf |