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» A discriminative model for semi-supervised learning
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AAAI
2008
13 years 11 months ago
Hidden Dynamic Probabilistic Models for Labeling Sequence Data
We propose a new discriminative framework, namely Hidden Dynamic Conditional Random Fields (HDCRFs), for building probabilistic models which can capture both internal and external...
Xiaofeng Yu, Wai Lam
ACIVS
2006
Springer
14 years 2 months ago
Discrete Choice Models for Static Facial Expression Recognition
In this paper we propose the use of Discrete Choice Analysis (DCA) for static facial expression classification. Facial expressions are described with expression descriptive units ...
Gianluca Antonini, Matteo Sorci, Michel Bierlaire,...
ECCV
2010
Springer
14 years 3 days ago
Modeling Temporal Structure of Decomposable Motion Segments for Activity Classification
Abstract. Much recent research in human activity recognition has focused on the problem of recognizing simple repetitive (walking, running, waving) and punctual actions (sitting up...
ACCV
2006
Springer
14 years 2 months ago
Probabilistic Modeling for Structural Change Inference
We view the task of change detection as a problem of object recognition from learning. The object is defined in a 3D space where the time is the 3rd dimension. We propose two com...
Wei Liu, Véronique Prinet
CVPR
2009
IEEE
1453views Computer Vision» more  CVPR 2009»
15 years 1 months ago
Learning Photometric Invariance From Diversified Color Model Ensembles
Color is a powerful visual cue for many computer vision applications such as image segmentation and object recognition. However, most of the existing color models depend on the i...
Jose M. Alvarez, Theo Gevers, Antonio M. Lopez