Optimising Perceived Distortion in Lossy Encoding of Dynamic Meshes

Development of geometry data compression techniques in the past years has been limited by the lack of a metric with proven correlation with human perception of mesh distortion. Many algorithms have been proposed, but usually the aim has been to minimise mean squared error, or some of its derivatives...

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Published inComputer graphics forum Vol. 30; no. 5; pp. 1439 - 1449
Main Authors Vasa, L, Petrik, O
Format Journal Article
LanguageEnglish
Published Oxford, UK Blackwell Publishing Ltd 01.08.2011
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Online AccessGet full text
ISSN0167-7055
1467-8659
DOI10.1111/j.1467-8659.2011.02018.x

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Abstract Development of geometry data compression techniques in the past years has been limited by the lack of a metric with proven correlation with human perception of mesh distortion. Many algorithms have been proposed, but usually the aim has been to minimise mean squared error, or some of its derivatives. In the field of dynamic mesh compression, the situation has changed with the recent proposal of the STED metric, which has been shown to capture the human perception of mesh distortion much better than previous metrics. In this paper we show how existing algorithms can be steered to provide optimal results with respect to this metric, and we propose a novel dynamic mesh compression algorithm, based on trajectory space PCA and Laplacian coordinates, specifically designed to minimise the newly proposed STED error. Our experiments show that using the proposed algorithm, we were able to reduce the required data rate by up to 50% while preserving the introduced STED error.
AbstractList Development of geometry data compression techniques in the past years has been limited by the lack of a metric with proven correlation with human perception of mesh distortion. Many algorithms have been proposed, but usually the aim has been to minimise mean squared error, or some of its derivatives. In the field of dynamic mesh compression, the situation has changed with the recent proposal of the STED metric, which has been shown to capture the human perception of mesh distortion much better than previous metrics. In this paper we show how existing algorithms can be steered to provide optimal results with respect to this metric, and we propose a novel dynamic mesh compression algorithm, based on trajectory space PCA and Laplacian coordinates, specifically designed to minimise the newly proposed STED error. Our experiments show that using the proposed algorithm, we were able to reduce the required data rate by up to 50% while preserving the introduced STED error.
Development of geometry data compression techniques in the past years has been limited by the lack of a metric with proven correlation with human perception of mesh distortion. Many algorithms have been proposed, but usually the aim has been to minimise mean squared error, or some of its derivatives. In the field of dynamic mesh compression, the situation has changed with the recent proposal of the STED metric, which has been shown to capture the human perception of mesh distortion much better than previous metrics. In this paper we show how existing algorithms can be steered to provide optimal results with respect to this metric, and we propose a novel dynamic mesh compression algorithm, based on trajectory space PCA and Laplacian coordinates, specifically designed to minimise the newly proposed STED error. Our experiments show that using the proposed algorithm, we were able to reduce the required data rate by up to 50% while preserving the introduced STED error.
Development of geometry data compression techniques in the past years has been limited by the lack of a metric with proven correlation with human perception of mesh distortion. Many algorithms have been proposed, but usually the aim has been to minimise mean squared error, or some of its derivatives. In the field of dynamic mesh compression, the situation has changed with the recent proposal of the STED metric, which has been shown to capture the human perception of mesh distortion much better than previous metrics. In this paper we show how existing algorithms can be steered to provide optimal results with respect to this metric, and we propose a novel dynamic mesh compression algorithm, based on trajectory space PCA and Laplacian coordinates, specifically designed to minimise the newly proposed STED error. Our experiments show that using the proposed algorithm, we were able to reduce the required data rate by up to 50% while preserving the introduced STED error. [PUBLICATION ABSTRACT]
Author Váša, L.
Petřík, O.
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– ident: e_1_2_8_13_2
  doi: 10.1109/TCSVT.2003.815173
– start-page: 126
  volume-title: SCA '03: Proceedings of the 2003 ACM SIGGRAPH/Eurographics symposium on Computer animation
  year: 2003
  ident: e_1_2_8_7_2
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Snippet Development of geometry data compression techniques in the past years has been limited by the lack of a metric with proven correlation with human perception of...
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SubjectTerms Algorithms
Approximate methods
Compressing
Computer Graphics [I.3.7]: Animation
Data compression
Distortion
Dynamics
Errors
Human
Image Processing And Computer Vision [I.4.2]: Compression(Coding)
Optimization
Perception
Perceptions
Studies
Title Optimising Perceived Distortion in Lossy Encoding of Dynamic Meshes
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Volume 30
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