A non-parametric hierarchical Bayesian framework is developed for designing a classifier, based on a mixture of simple (linear) classifiers. Each simple classifier is termed a loc...
Chunping Wang, Xuejun Liao, Lawrence Carin, David ...
This paper presents a new formulation of the problem of motion estimation which attempts to give solutions to classical problems in the field, such as detection of motion disconti...
We propose a generic computational framework for maintaining a discrete geometric structure defined by a collection of static and mobile objects. We assume that the mobile object...
David M. Mount, Nathan S. Netanyahu, Christine D. ...
A new time-sequential approach for motion layer extraction is presented. We assume that the scene can be described by a set of layers associated to affine motion models. In one o...
- We present a connectionist model that combines motions and language based on the behavioral experiences of a real robot. Two models of recurrent neural network with parametric bi...
Tetsuya Ogata, Masamitsu Murase, Jun Tani, Kazunor...