Recently, manifold learning has been widely exploited in pattern recognition, data analysis, and machine learning. This paper presents a novel framework, called Riemannian manifold...
We introduce a number of new results in the context of multi-view geometry from general algebraic curves. We start with the derivation of the extended Kruppa's equations whic...
Jeremy Yermiyahou Kaminski, Michael Fryers, Amnon ...
We review recent progress in the study of arrangements in computational and combinatorial geometry, and discuss several open problems and areas for further research. In this talk I...
This paper describes shear-image order ray casting, a new method for volume rendering. This method renders sampled data in three dimensions with image quality equivalent to the be...
Yin Wu, Vishal Bhatia, Hugh C. Lauer, Larry Seiler
In this paper we study a dynamic version of capacity maximization in the physical model of wireless communication. In our model, requests for connections between pairs of points i...