Figure-ground discrimination is an important problem in computer vision. Previous work usually assumes that the color distribution of the figure can be described by a low dimensio...
We present a general approach to model selection and regularization that exploits unlabeled data to adaptively control hypothesis complexity in supervised learning tasks. The idea ...
A new distance measure between probability density functions (pdfs) is introduced, which we refer to as the Laplacian pdf distance. The Laplacian pdf distance exhibits a remarkabl...
This paper considers the role of performance and area estimates from behavioral synthesis in design space exploration. We have developed a compilation system that automatically ma...
Detecting and segmenting moving objects in dynamic scenes is a hard but essential task in a number of applications such as surveillance. Most existing methods only give good resul...