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Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms sy...
CVPR
2006
IEEE
14 years 9 months ago
2006
IEEE
Activity recognition is an important issue in building intelligent monitoring systems. We address the recognition of multilevel activities in this paper via a conditional Markov r...
KDD
2009
ACM
14 years 8 months ago
2009
ACM
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
PAMI
2008
13 years 7 months ago
2008
We address the issue of classifying complex data. We focus on three main sources of complexity, namely, the high dimensionality of the observed data, the dependencies between these...
EMMCVPR
2005
Springer
2005
Springer
Exploiting Inference for Approximate Parameter Learning in Discriminative Fields: An Empirical Study
14 years 1 months ago
Abstract. Estimation of parameters of random field models from labeled training data is crucial for their good performance in many image analysis applications. In this paper, we p...