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...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2006
|
| Subjects: | |
| Online Access: | http://eprints.usm.my/14448/1/paper2.pdf http://eprints.usm.my/14448/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | 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.
|
|---|