Mixture modelling is a hot area in pattern recognition. Although most research in this area has focused on mixtures for continuous data, there are many pattern recognition tasks f...
We propose a novel mixtures of Gaussian processes model in which the gating function is interconnected with a probabilistic logical model, in our case Markov logic networks. In th...
Mixture models, such as Gaussian Mixture Model, have been widely used in many applications for modeling data. Gaussian mixture model (GMM) assumes that data points are generated fr...
Discriminative approaches for human pose estimation model the functional mapping, or conditional distribution, between image features and 3D pose. Learning such multi-modal models ...
Model-based clustering of motion trajectories can be posed as the problem of learning an underlying mixture density function whose components correspond to motion classes with dif...