<abstract xmlns="http://www.w3.org/1999/xhtml"><p> This work presents an analysis of Higher Order Singular Value Decomposition (HOSVD) applied to reduction of dimensionality of 3D mesh animations. Compression error is measured using three metrics (MSE, Hausdorff, MSDM). Results are compared with a method based on Principal Component Analysis (PCA) and presented on a set of animations with typical mesh deformations.</p></abstract>

This work presents an analysis of Higher Order Singular Value Decomposition (HOSVD) applied to reduction of dimensionality of 3D mesh animations. Compression error is measured using three metrics (MSE, Hausdorff, MSDM). Results are compared with a method based on Principal Component Analysis (PCA) and presented on a set of animations with typical mesh deformations.

Dimensionality Reduction of Dynamic Mesh Animations Using HO-SVD

Institute of Theoretical and Applied Informatics, Polish Academy of Sciences

Journal of Artificial Intelligence and Soft Computing Research

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Dimensionality Reduction of Dynamic Mesh Animations Using HO-SVD"}

This work presents an analysis of Higher Order Singular Value Decomposition (HOSVD) applied to reduction of dimensionality of 3D mesh animations. Compression...

Dimensionality Reduction of Dynamic Mesh Animations Using HO-SVD

Published Online: Dec 30, 2014

Page range: 277 - 289

DOI: https://doi.org/10.2478/jaiscr-2014-0020

© 2015

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.