This paper presents a novel approach to model the complex motion of human using a probabilistic autoregressive moving average model. The parameters of the model are adaptively tun...
Mohammad Hossein Ghaeminia, Amir Hossein Shabani, ...
Color-based tracking methods have proved to be efficient for their robustness qualities. The drawback of such global representation of an object is the lack of information on its s...
Many probabilistic models introduce strong dependencies between variables using a latent multivariate Gaussian distribution or a Gaussian process. We present a new Markov chain Mo...
Iain Murray, Ryan Prescott Adams, David J. C. MacK...
In this paper, we describe recent progress in i-vector based speaker verification. The use of universal background models (UBM) with full-covariance matrices is suggested and tho...
Pavel Matejka, Ondrej Glembek, Fabio Castaldo, M. ...
Clustering is a basic task in a variety of machine learning applications. Partitioning a set of input vectors into compact, wellseparated subsets can be severely affected by the p...
Pedro A. Forero, Vassilis Kekatos, Georgios B. Gia...