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...

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Bibliographic Details
Main Authors: Mashor, M Y, Osman, M K, Arshad, M R
Format: Conference or Workshop Item
Language:English
Published: 2006
Subjects:
Online Access:http://eprints.usm.my/14448/1/paper2.pdf
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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
collection USM
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 2024-03-06T14:08:40Z
format Conference or Workshop Item
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institution Universiti Sains Malaysia
language English
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publishDate 2006
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spelling usm.eprints-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/14448/1/paper2.pdf
work_keys_str_mv AT mashormy 3dobjectrecognitionusingmultipleviewsandneuralnetworks
AT osmanmk 3dobjectrecognitionusingmultipleviewsandneuralnetworks
AT arshadmr 3dobjectrecognitionusingmultipleviewsandneuralnetworks