We present a novel family of data-driven linear transformations, aimed at visualizing multivariate data in a low-dimensional space in a way that optimally preserves the structure ...
We present a new approach aimed at understanding the structure of connections in edge-bundling layouts. We combine the advantages of edge bundles with a bundle-centric simplified ...
Abstract. We present a framework for combining automated and interactive visual analysis techniques for use on high-resolution biomechanical data. Analyzing the complex 3D motion o...
Scott Spurlock, Remco Chang, Xiaoyu Wang, George A...
The state of the art for large database object retrieval in images is based on quantizing descriptors of interest points into visual words. High similarity between matching image r...
Our ability to accumulate large, complex (multivariate) data sets has far exceeded our ability to effectively process them in search of patterns, anomalies, and other interesting ...
Ying-Huey Fua, Matthew O. Ward, Elke A. Rundenstei...