BTF Compression via Sparse Tensor Decomposition

Simple item page
dc.contributor.authorRuiters, Rolanden_US
dc.contributor.authorKlein, Reinharden_US
dc.date.accessioned2015-02-23T14:56:10Z
dc.date.available2015-02-23T14:56:10Z
dc.date.issued2009en_US
dc.description.abstractIn this paper, we present a novel compression technique for Bidirectional Texture Functions based on a sparse tensor decomposition. We apply the K-SVD algorithm along two different modes of a tensor to decompose it into a small dictionary and two sparse tensors. This representation is very compact, allowing for considerably better compression ratios at the same RMS error than possible with current compression techniques like PCA, N-mode SVD and Per Cluster Factorization. In contrast to other tensor decomposition based techniques, the use of a sparse representation achieves a rendering performance that is at high compression ratios similar to PCA based methods.en_US
dc.description.number4en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume28en_US
dc.identifier.doi10.1111/j.1467-8659.2009.01495.xen_US
dc.identifier.issn1467-8659en_US
dc.identifier.pages1181-1188en_US
dc.identifier.urihttps://doi.org/10.1111/j.1467-8659.2009.01495.xen_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltden_US
dc.titleBTF Compression via Sparse Tensor Decompositionen_US
Files
Collections
28-Issue 4
EGSR09: 20th Eurographics Symposium on Rendering