Parallelized Matrix Factorization for fast BTF Compression

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dc.contributor.authorRuiters, Rolanden_US
dc.contributor.authorRump, Martinen_US
dc.contributor.authorKlein, Reinharden_US
dc.contributor.editorKurt Debattista and Daniel Weiskopf and Joao Combaen_US
dc.date.accessioned2014-01-26T16:47:47Z
dc.date.available2014-01-26T16:47:47Z
dc.date.issued2009en_US
dc.description.abstractDimensionality reduction methods like Principal Component Analysis (PCA) have become commonplace for the compression of large datasets in computer graphics. One important application is the compression of Bidirectional Texture Functions (BTF). However, the use of such techniques has still many limitations that arise from the large size of the input data which results in impractically high compression times. In this paper, we address these shortcomings and present a method which allows for efficient parallelized computation of the PCA of a large BTF matrix. The matrix is first split into several blocks for which the PCA can be performed independently and thus in parallel. We scale the single subproblems in such a way, that they can be solved in-core using the EM-PCA algorithm. This allows us to perform the calculation on current GPUs exploiting their massive parallel computing power. The eigenspaces determined for the individual blocks are then merged to obtain the PCA of the whole dataset. This way nearly arbitrarily sized matrices can be processed considerably faster than by serial algorithms. Thus, BTFs with much higher spatial and angular resolution can be compressed in reasonable time.en_US
dc.description.seriesinformationEurographics Symposium on Parallel Graphics and Visualizationen_US
dc.identifier.isbn978-3-905674-15-6en_US
dc.identifier.issn1727-348Xen_US
dc.identifier.urihttps://doi.org/10.2312/EGPGV/EGPGV09/025-032en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism-Color, shading, shadowing, and texture G.4 [Mathematics of Computing]: Mathematical Software-Parallel and vector implementationsen_US
dc.titleParallelized Matrix Factorization for fast BTF Compressionen_US
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EGPGV09: Eurographics Symposium on Parallel Graphics and Visualization