In this paper we present a technique for the tracking of textured almost planar object. The target is modeled as a noisy planar cloud of points. The tracking is led with an approp...
This paper proposes a statistic framework for segmenting textured areas over real images by discriminant snakes. Our active contour model has the ability to learn different textur...
In this paper, we establish a theoretical framework for a new concept of scheduling called soft scheduling. In contrasts to the traditional schedulers referred as hard schedulers,...
We consider a setting for discriminative semisupervised learning where unlabeled data are used with a generative model to learn effective feature representations for discriminativ...
Kernel learning plays an important role in many machine learning tasks. However, algorithms for learning a kernel matrix often scale poorly, with running times that are cubic in t...