Classifying pictures into one of several semantic categories is a classical image understanding problem. In this paper, we present a stratified approach to both binary (outdoor-in...
Image-based representations of an object profit from known geometry. The more accurate this geometry is known, the better corresponding pixels in the different images can be align...
We present the Optimizing Control Variate (OCV) estimator, a new estimator for Monte Carlo rendering. Based upon a deterministic sampling framework, OCV allows multiple importance...
Shaohua Fan, Stephen Chenney, Bo Hu, Kam-Wah Tsui,...
In this work a new method to retrieve images with similar lighting conditions is presented. It is based on automatic clustering and automatic indexing. Our proposal belongs to Con...
We propose a hybrid particle and texture based approach for the visualization of time-dependent vector fields. The underlying spacetime framework builds a dense vector field rep...
Daniel Weiskopf, Frederik Schramm, Gordon Erlebach...