Memory and network bandwidth are decisive bottlenecks when handling high-resolution
multidimensional data sets in visualization applications, and they increasingly demand …

Interactive visual analysis of large and complex volume datasets is an ongoing and
challenging problem. We tackle this challenge in the context of state‐of‐the‐art out‐of‐core …

Tensor decompositions, in particular the Tucker model, are a powerful family of techniques
for dimensionality reduction and are being increasingly used for compactly encoding large …

In this article we present a novel dictionary learning framework designed for compression
and sampling of light fields and light field videos. Unlike previous methods, where a single …

The BTF data structure was a breakthrough for appearance modeling in computer graphics.
More research is needed though to make BTFs practical in rendering applications. We …

As modern high-resolution imaging devices allow to acquire increasingly large and complex
volume data sets, their effective and compact representation for visualization becomes a …

Recent growth in camera/video technology, alongside the development of visual data
aggregation and transmission algorithms, has facilitated a new kind of WSN called the …

The rapid expansion of social media has notably transformed political communication, with
politicians and activists increasingly adopting multimedia formats to disseminate their …

This article presents a generalized sparse multilinear model, namely multiway K-clustered
tensor approximation (MK-CTA), for synthesizing photorealistic 3D images from large-scale …

The ongoing advances in computational photography have introduced a range of new
imaging techniques for capturing multidimensional visual data such as light fields, BRDFs …