76 search results - page 2 / 16 » Exploring Features in a Bayesian Framework for Material Reco... |
CVPR
1999
IEEE
13 years 9 months ago
1999
IEEE
We introduce an approach to feature-based object recognition, using maximum a posteriori (MAP) estimation under a Markov random field (MRF) model. This approach provides an effici...
ICMI
2009
Springer
13 years 3 months ago
2009
Springer
Affect sensitivity is of the utmost importance for a robot companion to be able to display socially intelligent behaviour, a key requirement for sustaining long-term interactions ...
ICMCS
2007
IEEE
13 years 11 months ago
2007
IEEE
Contextual information is important for sequence modeling. Hidden Markov Models (HMMs) and extensions, which have been widely used for sequence modeling, make simplifying, often u...
ICB
2009
Springer
13 years 11 months ago
2009
Springer
In this paper, a Bayesian method for face recognition is proposed based on Markov Random Fields (MRF) modeling. Constraints on image features as well as contextual relationships be...
CVPR
2000
IEEE
13 years 9 months ago
2000
IEEE
We present a framework for tracking rigid objects based on an adaptive Bayesian recognition technique that incorporates dependencies between object features. At each frame we fin...