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» A probabilistic framework for object recognition in video
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ICCV
2007
IEEE
14 years 9 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
ICCV
2003
IEEE
14 years 9 months ago
Statistical Background Subtraction for a Mobile Observer
Statistical background modelling and subtraction has proved to be a popular and effective class of algorithms for segmenting independently moving foreground objects out from a sta...
Eric Hayman, Jan-Olof Eklundh
CVPR
2007
IEEE
14 years 9 months ago
Groupwise Shape Registration on Raw Edge Sequence via A Spatio-Temporal Generative Model
Groupwise shape registration of raw edge sequence is addressed. Automatically extracted edge maps are treated as noised input shape of the deformable object and their registration...
Huijun Di, Rao Naveed Iqbal, Guangyou Xu, Linmi Ta...
CVPR
2008
IEEE
14 years 9 months ago
Recognizing human actions using multiple features
In this paper, we propose a framework that fuses multiple features for improved action recognition in videos. The fusion of multiple features is important for recognizing actions ...
Jingen Liu, Saad Ali, Mubarak Shah
JMLR
2010
169views more  JMLR 2010»
13 years 2 months ago
Factored 3-Way Restricted Boltzmann Machines For Modeling Natural Images
Deep belief nets have been successful in modeling handwritten characters, but it has proved more difficult to apply them to real images. The problem lies in the restricted Boltzma...
Marc'Aurelio Ranzato, Alex Krizhevsky, Geoffrey E....