Dimensionality reduction for computer facial animation

This paper describes the usage of dimensionality reduction techniques for computer facial animation. Techniques such as Principal Components Analysis (PCA), Expectation–Maximization (EM) algorithm for PCA, Multidimensional Scaling (MDS), and Locally Linear Embedding (LLE) are compared for the purpos...

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Main Author:	Tsai, Flora S.
Other Authors:	School of Electrical and Electronic Engineering
Format:	Article
Language:	English
Published:	2013
Subjects:	DRNTU::Engineering::Electrical and electronic engineering
Online Access:	https://hdl.handle.net/10356/84786 http://hdl.handle.net/10220/11106
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Institution:	Nanyang Technological University
Language:	English

id	sg-ntu-dr.10356-84786
record_format	dspace
spelling	sg-ntu-dr.10356-847862020-03-07T13:57:29Z Dimensionality reduction for computer facial animation Tsai, Flora S. School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering This paper describes the usage of dimensionality reduction techniques for computer facial animation. Techniques such as Principal Components Analysis (PCA), Expectation–Maximization (EM) algorithm for PCA, Multidimensional Scaling (MDS), and Locally Linear Embedding (LLE) are compared for the purpose of facial animation of different emotions. The experimental results on our facial animation data demonstrate the usefulness of dimensionality reduction techniques for both space and time reduction. In particular, the EMPCA algorithm performed especially well in our dataset, with negligible error of only 1–2%. 2013-07-10T06:14:05Z 2019-12-06T15:51:09Z 2013-07-10T06:14:05Z 2019-12-06T15:51:09Z 2011 2011 Journal Article https://hdl.handle.net/10356/84786 http://hdl.handle.net/10220/11106 10.1016/j.eswa.2011.10.018 en Expert systems with applications © 2011 Elsevier Ltd.
institution	Nanyang Technological University
building	NTU Library
country	Singapore
collection	DR-NTU
language	English
topic	DRNTU::Engineering::Electrical and electronic engineering
spellingShingle	DRNTU::Engineering::Electrical and electronic engineering Tsai, Flora S. Dimensionality reduction for computer facial animation
description	This paper describes the usage of dimensionality reduction techniques for computer facial animation. Techniques such as Principal Components Analysis (PCA), Expectation–Maximization (EM) algorithm for PCA, Multidimensional Scaling (MDS), and Locally Linear Embedding (LLE) are compared for the purpose of facial animation of different emotions. The experimental results on our facial animation data demonstrate the usefulness of dimensionality reduction techniques for both space and time reduction. In particular, the EMPCA algorithm performed especially well in our dataset, with negligible error of only 1–2%.
author2	School of Electrical and Electronic Engineering
author_facet	School of Electrical and Electronic Engineering Tsai, Flora S.
format	Article
author	Tsai, Flora S.
author_sort	Tsai, Flora S.
title	Dimensionality reduction for computer facial animation
title_short	Dimensionality reduction for computer facial animation
title_full	Dimensionality reduction for computer facial animation
title_fullStr	Dimensionality reduction for computer facial animation
title_full_unstemmed	Dimensionality reduction for computer facial animation
title_sort	dimensionality reduction for computer facial animation
publishDate	2013
url	https://hdl.handle.net/10356/84786 http://hdl.handle.net/10220/11106
_version_	1681049955697950720

Dimensionality reduction for computer facial animation

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