We advocate the use of Gaussian Process Dynamical Models (GPDMs) for learning human pose and motion priors for 3D people tracking. A GPDM provides a lowdimensional embedding of hu...
This paper presents a probabilistic algorithm for segmenting and recognizing text embedded in video sequences. The algorithm approximates the posterior distribution of segmentatio...
In this paper, we systematically define three transaction level TLMs), which reside at different levels of abstraction between the functional and the implementation model of a DSP...
Moment matching is a popular means of parametric density estimation. We extend this technique to nonparametric estimation of mixture models. Our approach works by embedding distri...
The design of modern complex embedded systems require a high level of abstraction of the design. The SimnML[1] is a specification language to model processors for such designs. Se...