99 search results - page 2 / 20 » Learning Hidden Markov Models with Distributed State Represe... |
CVIU
2004
13 years 5 months ago
2004
We present the use of layered probabilistic representations for modeling human activities, and describe how we use the representation to do sensing, learning, and inference at mul...
ICIP
2006
IEEE
14 years 7 months ago
2006
IEEE
In this paper we propose a new framework for modeling 2D shapes. A shape is first described by a sequence of local features (e.g., curvature) of the shape boundary. The resulting ...
ICIP
2007
IEEE
14 years 7 months ago
2007
IEEE
We develop a hierarchical, nonparametric statistical model for wavelet representations of natural images. Extending previous work on Gaussian scale mixtures, wavelet coefficients ...
ECML
2005
Springer
13 years 11 months ago
2005
Springer
We propose in this paper a novel approach to the induction of the structure of Hidden Markov Models. The induced model is seen as a lumped process of a Markov chain. It is construc...
CIVR
2008
Springer
13 years 7 months ago
2008
Springer
In this paper, a motion-based approach for detecting highlevel semantic events in video sequences is presented. Its main characteristic is its generic nature, i.e. it can be direc...