The variation of facial texture and surface due to the change of expression is an important cue for analyzing and modeling facial expressions. In this paper, we propose a new appr...
In this paper we introduce a new deformable model, called eigensnake, for segmentation of elongated structures in a probabilistic framework. Instead of snake attraction by speci...
Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...
While significant effort has been put into annotating linguistic resources for several languages, there are still many left that have only small amounts of such resources. This p...
The categorization of our environment into feature types is an essential prerequisite for cartography, geographic information retrieval, routing applications, spatial decision supp...