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» Statistical Models of Appearance for Computer Vision
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131
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ICCV
2007
IEEE
16 years 5 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
109
Voted
ICPR
2002
IEEE
15 years 8 months ago
Motion Prediction Using VC-Generalization Bounds
This paper describes a novel application of Statistical Learning Theory (SLT) for motion prediction. SLT provides analytical VC-generalization bounds for model selection; these bo...
Harry Wechsler, Zoran Duric, Fayin Li, Vladimir Ch...
CVPR
2010
IEEE
16 years 3 days ago
Spike Train Driven Dynamical Models for Human Actions
We investigate dynamical models of human motion that can support both synthesis and analysis tasks. Unlike coarser discriminative models that work well when action classes are ...
Michalis Raptis, Kamil Wnuk , Stefano Soatto
145
Voted
EMMCVPR
2005
Springer
15 years 9 months ago
Object Categorization by Compositional Graphical Models
This contribution proposes a compositionality architecture for visual object categorization, i.e., learning and recognizing multiple visual object classes in unsegmented, cluttered...
Björn Ommer, Joachim M. Buhmann
131
Voted
PAMI
2006
178views more  PAMI 2006»
15 years 3 months ago
Learning Nonlinear Image Manifolds by Global Alignment of Local Linear Models
Appearance-based methods, based on statistical models of the pixel values in an image (region) rather than geometrical object models, are increasingly popular in computer vision. I...
Jakob J. Verbeek