In this paper we offer several new insights and techniques for effectively using color and texture to simultaneously convey information about multiple 2D scalar and vector distrib...
Timothy Urness, Victoria Interrante, Ivan Marusic,...
We investigate the use of linear and nonlinear principal manifolds for learning low-dimensional representations for visual recognition. Several leading techniques: Principal Compo...
This paper describes a new representation for the audio and visual information in a video signal. We reduce the dimensionality of the signals with singular-value decompositions (S...
With the rapid development in graphics hardware and volume rendering techniques, many volumetric datasets can now be rendered in real time on a standard PC equipped with a commodi...
This paper presents a novel object recognition approach based on range images. Due to its insensitivity to illumination, range data is well suited for reliable silhouette extracti...