In this paper, we propose an e cient technique for the animation of exible thin objects. Massspring model was employed to represent the exible objects. Many techniques have used t...
Deep Belief Networks (DBNs) are multi-layer generative models. They can be trained to model windows of coefficients extracted from speech and they discover multiple layers of fea...
Abdel-rahman Mohamed, Tara N. Sainath, George Dahl...
A probabilistic method for tracking 3D articulated human figures in monocular image sequences is presented. Within a Bayesian framework, we define a generative model of image appea...
Hedvig Sidenbladh, Michael J. Black, David J. Flee...
Recently, a new generation of adaptive process management technology has emerged, which enables dynamic changes of composite services and process models respectively. This, in tur...
We introduce dynamic correlated topic models (DCTM) for analyzing discrete data over time. This model is inspired by the hierarchical Gaussian process latent variable models (GP-L...