Friday, 24 June 2016
11:00 – 12:00 in Room 403
Rafael Ballester-Ripoll, University of Zurich
Tensor Decomposition in Graphics and Interactive Visualization
Tensor decomposition is an emerging framework for manipulating and visualizing large and high-dimensional data sets, and is gaining momentum in recent years among the graphics and visual computing communities. Tensor compression usually outperforms more traditional approaches such as the Fourier and wavelet transforms, and its advantage grows larger the higher the dimensionality. Visual data sets (image stacks, computer tomography scans, time varying data) often possess a relatively low-rank tensor structure, which allows many efficient operations in the tensor-compressed domain. Furthermore, there is an increasing number of algorithms for tensor completion and black-box sampling, with applications in sparse sampling and interpolation. Thanks to these combined properties, tensor methods have found concrete applications in volume and photorealistic material rendering, interactive scientific visualization, texture synthesis, image/volume completion, and more. In this talk I will overview the most popular decomposition models (canonical, Tucker and the more recent tensor train), discuss the latest applications and my current research on tensor-based graphics and visualization, and outline future trends in these areas.