Articles liés à Recognizing Techniques for 3D Objects on a Scene

Recognizing Techniques for 3D Objects on a Scene - Couverture souple

Hussain, Abadal-Salam T.

 
9783639512960: Recognizing Techniques for 3D Objects on a Scene
Couverture souple
ISBN 10 : 3639512960 ISBN 13 : 9783639512960
Editeur : Scholar's Press, 2013

Synopsis

Aim of this book: To propose a method to recognise 3D object from a single silhouette image. To recognise an object many problems must be solved like size change, translation, rotation around the three axes, partial occlusion, low intensity of light as well as the deformation of the shape. We propose to use the invariant Fourier descriptors coefficients from the contour of the projected area of the object and back propagation neural network. We made use of Fourier descriptors coefficients and back propagation neural network with different numbers of hidden layers to build the optimal classifier of 3D pattern from a single silhouette image. The recognised objects are exposed to different intensities of light, are partially occluded, with size change, translation, rotation about all the axes and we used also deformed shapes. For an enhancement of the results and acceleration of learning and recognition, a principal component analyser (PCA) have been used. The Fourier descriptors are compressed by PCA, in order to be fed to the neural network.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

Aim of this book: To propose a method to recognise 3D object from a single silhouette image. To recognise an object many problems must be solved like size change, translation, rotation around the three axes, partial occlusion, low intensity of light as well as the deformation of the shape. We propose to use the invariant Fourier descriptors coefficients from the contour of the projected area of the object and back propagation neural network. We made use of Fourier descriptors coefficients and back propagation neural network with different numbers of hidden layers to build the optimal classifier of 3D pattern from a single silhouette image. The recognised objects are exposed to different intensities of light, are partially occluded, with size change, translation, rotation about all the axes and we used also deformed shapes. For an enhancement of the results and acceleration of learning and recognition, a principal component analyser (PCA) have been used. The Fourier descriptors are compressed by PCA, in order to be fed to the neural network.

Biographie de l'auteur

PhD, Senior Lecturer (2007-2012), HND (BTEC-Edexcel, UK), SIT, UAE. Faculty lecturer - Uni. of Sharjah & Ittihad Uni., UAE (2002-2007). GCE (UK), B.Eng.(RNEC, UK), MSc Electronics Eng. (USTO, Algeria), PhD Mechatronics Eng., (UniMAP), Malaysia & PhD in Management (Mexico).

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
Scholar's Press
Date d'édition
2013
Langue
anglais
ISBN 10 
3639512960
ISBN 13 
9783639512960
Reliure
Broché
Nombre de pages
156
Coordonnées du fabricant
non disponible
Personne responsable
non disponible