Speech has a property that the speech unit preceding a speech pause tends to lengthen. This work presents the use of a dynamic Bayesian network to model the prepausal lengthening ...
Ning Ma, Chris Bartels, Jeff A. Bilmes, Phil Green
We propose a new approach to estimate gait kinematics from image sequences taken by a monocular uncalibrated camera. This approach involves two generative models for gait represen...
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...
Probabilistic models have been previously shown to be efficient and effective for modeling and recognition of human motion. In particular we focus on methods which represent the h...
Inference of latent variables from complicated data is one important problem in data mining. The high dimensionality and high complexity of real world data often make accurate infe...