204 search results - page 16 / 41 » Conditional Random Fields for Object Recognition |
211
click to vote
Book
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...
CVIU
2006
14 years 9 months ago
2006
We present algorithms for recognizing human motion in monocular video sequences, based on discriminative Conditional Random Field (CRF) and Maximum Entropy Markov Models (MEMM). E...
ECCV
1994
Springer
15 years 1 months ago
1994
Springer
A variety of computer vision problems can be optimally posed as Bayesian labeling in which the solution of a problem is dened as the maximum a posteriori (MAP) probability estimate...
INLG
2010
Springer
14 years 7 months ago
2010
Springer
We describe our contribution to the Generation Challenge 2010 for the tasks of Named Entity Recognition and coreference detection (GREC-NER). To extract the NE and the referring e...
CVPR
2007
IEEE
15 years 11 months ago
2007
IEEE
We describe an unsupervised method to segment objects detected in images using a novel variant of an interest point template, which is very efficient to train and evaluate. Once a...