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| Type | Conference or Workshop Paper |
| Scope | Discipline-based scholarship |
| Published in Proceedings | No |
| Title | Tensor Decomposition Methods in Visual Computing |
| Organization Unit | |
| Authors |
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| Presentation Type | other |
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| Event Title | IEEE Visualization Tutorials |
| Event Type | conference |
| Event Location | Baltimore, USA |
| Event Start Date | October 23 - 2016 |
| Event End Date | October 28 - 2016 |
| Place of Publication | Baltimore, USA |
| Abstract Text | Initially proposed as an extension of the concept of matrix decomposition for three and more dimensions, tensor decompo- sitions have found numerous applications in visualization and visual computing. They constitute a powerful mathematical framework for compactly representing and manipulating dense data fields, especially in many dimensions. This course will introduce the most popular decomposition models and showcase emerging tensor methods for compression, interactive visualization, texture synthesis, denoising, and multidimensional inpainting. Multidimensional visual data types of interest include image and geometry ensembles, hyperspectral images, volumes and corresponding time-varying data. |
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