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» A Framework for Representing Moving Objects
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ICCV
2007
IEEE
15 years 11 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
MIR
2004
ACM
236views Multimedia» more  MIR 2004»
15 years 3 months ago
Boosting contextual information in content-based image retrieval
We present a new framework for characterizing and retrieving objects in cluttered scenes. This CBIR system is based on a new representation describing every object taking into acc...
Jaume Amores, Nicu Sebe, Petia Radeva, Theo Gevers...
CVPR
2009
IEEE
2358views Computer Vision» more  CVPR 2009»
16 years 5 months ago
Pictorial Structures Revisited: People Detection and Articulated Pose Estimation
Non-rigid object detection and articulated pose estimation are two related and challenging problems in computer vision. Numerous models have been proposed over the years and oft...
Mykhaylo Andriluka (TU Darmstadt), Stefan Roth (TU...
CVPR
2005
IEEE
15 years 11 months ago
Fast Spatial Pattern Discovery Integrating Boosting with Constellations of Contextual Descriptors
We present a novel approach for fast object class recognition incorporating contextual information into boosting. The object is represented as a constellation of generalized corre...
Jaume Amores, Nicu Sebe, Petia Radeva
ISICT
2003
14 years 11 months ago
Topic maps for context management
Abstract. The advent of context-aware computing requires a new paradigm in information management. Context information in a computing environment will take the form of disparate an...
Ruaidhri Power