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3D object recognition system using multiple views and cascaded multilayered perceptron network

Proceeding of The International Conference on Computer Graphics, Imaging and Visualization 2004 at Singapore on 1 December 2004 through 3 December 2004. Link to publisher's homepage at http://ezproxy.unimap.edu.my:2080/Xplore/dynhome.jsp?tag=1

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Bibliographic Details
Main Authors: Muhammad Khusairi, Osman, Mohd Yusoff, Mashor, Prof. Dr., Mohd Rizal, Arshad
Other Authors: khusairi@eng.usm.my
Format: Working Paper
Language:English
Published: IEEE Conference Publications 2014
Subjects:
Object recognition
Cascade Multilayered Perceptron (c-MLP)
Three dimensional (3d) object recognition systems
Vision systems
Online Access:http://dspace.unimap.edu.my:80/dspace/handle/123456789/35051
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spelling my.unimap-350512014-06-04T04:46:10Z 3D object recognition system using multiple views and cascaded multilayered perceptron network Muhammad Khusairi, Osman Mohd Yusoff, Mashor, Prof. Dr. Mohd Rizal, Arshad khusairi@eng.usm.my yusoff@unimap.edu.my rizal@eng.usm.my Object recognition Cascade Multilayered Perceptron (c-MLP) Three dimensional (3d) object recognition systems Vision systems Proceeding of The International Conference on Computer Graphics, Imaging and Visualization 2004 at Singapore on 1 December 2004 through 3 December 2004. Link to publisher's homepage at http://ezproxy.unimap.edu.my:2080/Xplore/dynhome.jsp?tag=1 This paper proposes an effective method for recognition and classification of 3D objects using multiple views technique and neural networks system. In the processing stage, we propose to use 2D moment invariants as the features for modeling 3D objects. 2D moments have been commonly used for 2D object recognition. However, we have proved that with some adaptation to multiple views technique, 2D moments are sufficient to model 3D objects. In addition, the simplicity of 2D moments calculation reduces the processing time for feature extraction, hence increases the system efficiency. In the recognition stage, we propose a cascaded multilayered perceptron (c-MLP) network for matching and classification. The c-MLP contains two MLP networks which are arranged in a serial combination. This proposed method has been tested using two groups of object, polyhedral and free-form objects. We also compare our method with standard MLP network. Our results show that the proposed method can successfully be applied to 3D object recognition. In addition, the proposed network also achieved better performance and faster convergence rate compared to the than standard MLP. 2014-06-04T04:21:32Z 2014-06-04T04:21:32Z 2004-12 Working Paper p. 1011-1015 0-7803-8643-4 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1460727&tag=1 http://dspace.unimap.edu.my:80/dspace/handle/123456789/35051 http://dx.doi.org/10.1109/ICCIS.2004.1460727 en Proceeding of The IEEE Conference on Cybernetics and Intelligent Systems 2004; IEEE Conference Publications
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Object recognition
Cascade Multilayered Perceptron (c-MLP)
Three dimensional (3d) object recognition systems
Vision systems
spellingShingle Object recognition
Cascade Multilayered Perceptron (c-MLP)
Three dimensional (3d) object recognition systems
Vision systems
Muhammad Khusairi, Osman
Mohd Yusoff, Mashor, Prof. Dr.
Mohd Rizal, Arshad
3D object recognition system using multiple views and cascaded multilayered perceptron network
description Proceeding of The International Conference on Computer Graphics, Imaging and Visualization 2004 at Singapore on 1 December 2004 through 3 December 2004. Link to publisher's homepage at http://ezproxy.unimap.edu.my:2080/Xplore/dynhome.jsp?tag=1
author2 khusairi@eng.usm.my
author_facet khusairi@eng.usm.my
Muhammad Khusairi, Osman
Mohd Yusoff, Mashor, Prof. Dr.
Mohd Rizal, Arshad
format Working Paper
author Muhammad Khusairi, Osman
Mohd Yusoff, Mashor, Prof. Dr.
Mohd Rizal, Arshad
author_sort Muhammad Khusairi, Osman
title 3D object recognition system using multiple views and cascaded multilayered perceptron network
title_short 3D object recognition system using multiple views and cascaded multilayered perceptron network
title_full 3D object recognition system using multiple views and cascaded multilayered perceptron network
title_fullStr 3D object recognition system using multiple views and cascaded multilayered perceptron network
title_full_unstemmed 3D object recognition system using multiple views and cascaded multilayered perceptron network
title_sort 3d object recognition system using multiple views and cascaded multilayered perceptron network
publisher IEEE Conference Publications
publishDate 2014
url http://dspace.unimap.edu.my:80/dspace/handle/123456789/35051
_version_ 1643797311816466432
score 13.214268

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