Learning from streams of evolving and unbounded data is an important problem, for example in visual surveillance or internet scale data. For such large and evolving real-world data...
Chen Change Loy, Timothy M. Hospedales, Tao Xiang,...
Establishing the correct correspondence between features in an image set remains a challenging problem amongst computer vision researchers. In fact, the combinatorial nature of fe...
We describe a system that provides query based associative access to the contents of distributed information servers. In typical distributed information systems there are so many o...
Mark A. Sheldon, Andrzej Duda, Ron Weiss, James O'...
We present a novel Object Recognition approach based on affine invariant regions. It actively counters the problems related to the limited repeatability of the region detectors, an...
Vittorio Ferrari, Tinne Tuytelaars, Luc J. Van Goo...
Many large scale physics-based simulations which take place on PC clusters or supercomputers produce huge amounts of data including vector fields. While these vector data such as ...