Geometry Compression for 3D Polygonal Models using a Neural Network

Three dimensional models are commonly used in computer graphics and 3D modeling characters in animation movies and games. 3D objects are more complex to handle than other multimedia data due to the fact that various representations exist for the same object, yielding a number of difficulties, among...

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Main Authors: Rumman, N., El-Seoud, S., Khatatneh, K., Gütl, Christian
Format: Journal Article
Published: Foundation of Computer Science 2010
Online Access:http://hdl.handle.net/20.500.11937/26017
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author Rumman, N.
El-Seoud, S.
Khatatneh, K.
Gütl, Christian
author_facet Rumman, N.
El-Seoud, S.
Khatatneh, K.
Gütl, Christian
author_sort Rumman, N.
building Curtin Institutional Repository
collection Online Access
description Three dimensional models are commonly used in computer graphics and 3D modeling characters in animation movies and games. 3D objects are more complex to handle than other multimedia data due to the fact that various representations exist for the same object, yielding a number of difficulties, among of which are the distinct sources of 3D data. Research work in the field of three dimensional environments is represented by a broad spectrum of applications. In this paper we restrict ourselves only on how to do compression using a neural network in order to minimize the size of 3D models for making transmission over networks much faster. The main objective behind this compression is to simplify the 3D model and make handling the large size of 3d objects much easier for other processes. Even the process of rendering, digital watermarking, etc., will be faster and more efficient.
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institution Curtin University Malaysia
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publishDate 2010
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spelling curtin-20.500.11937-260172017-01-30T12:51:17Z Geometry Compression for 3D Polygonal Models using a Neural Network Rumman, N. El-Seoud, S. Khatatneh, K. Gütl, Christian Three dimensional models are commonly used in computer graphics and 3D modeling characters in animation movies and games. 3D objects are more complex to handle than other multimedia data due to the fact that various representations exist for the same object, yielding a number of difficulties, among of which are the distinct sources of 3D data. Research work in the field of three dimensional environments is represented by a broad spectrum of applications. In this paper we restrict ourselves only on how to do compression using a neural network in order to minimize the size of 3D models for making transmission over networks much faster. The main objective behind this compression is to simplify the 3D model and make handling the large size of 3d objects much easier for other processes. Even the process of rendering, digital watermarking, etc., will be faster and more efficient. 2010 Journal Article http://hdl.handle.net/20.500.11937/26017 Foundation of Computer Science fulltext
spellingShingle Rumman, N.
El-Seoud, S.
Khatatneh, K.
Gütl, Christian
Geometry Compression for 3D Polygonal Models using a Neural Network
title Geometry Compression for 3D Polygonal Models using a Neural Network
title_full Geometry Compression for 3D Polygonal Models using a Neural Network
title_fullStr Geometry Compression for 3D Polygonal Models using a Neural Network
title_full_unstemmed Geometry Compression for 3D Polygonal Models using a Neural Network
title_short Geometry Compression for 3D Polygonal Models using a Neural Network
title_sort geometry compression for 3d polygonal models using a neural network
url http://hdl.handle.net/20.500.11937/26017