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» Bayesian learning of joint distributions of objects
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ECCV
2006
Springer
16 years 6 months ago
Conditional Infomax Learning: An Integrated Framework for Feature Extraction and Fusion
The paper introduces a new framework for feature learning in classification motivated by information theory. We first systematically study the information structure and present a n...
Dahua Lin, Xiaoou Tang
ICCV
2007
IEEE
16 years 6 months ago
Learning Higher-order Transition Models in Medium-scale Camera Networks
We present a Bayesian framework for learning higherorder transition models in video surveillance networks. Such higher-order models describe object movement between cameras in the...
Ryan Farrell, David S. Doermann, Larry S. Davis
ICIP
2008
IEEE
16 years 5 months ago
Implicit spatial inference with sparse local features
This paper introduces a novel way to leverage the implicit geometry of sparse local features (e.g. SIFT operator) for the purposes of object detection and segmentation. A two-clas...
Deirdre O'Regan, Anil C. Kokaram
ICCV
2007
IEEE
16 years 6 months ago
Optimization and Learning for Registration of Moving Dynamic Textures
We address the problem of registering a sequence of images in a moving dynamic texture video. This involves optimization with respect to camera motion, the average image, and the ...
Junzhou Huang, Xiaolei Huang, Dimitris N. Metaxas
ICPR
2006
IEEE
16 years 5 months ago
Combining Generative and Discriminative Methods for Pixel Classification with Multi-Conditional Learning
It is possible to broadly characterize two approaches to probabilistic modeling in terms of generative and discriminative methods. Provided with sufficient training data the discr...
B. Michael Kelm, Chris Pal, Andrew McCallum