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» Learning Mid-Level Features For Recognition
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UMUAI
1998
157views more  UMUAI 1998»
13 years 7 months ago
Bayesian Models for Keyhole Plan Recognition in an Adventure Game
We present an approach to keyhole plan recognition which uses a dynamic belief (Bayesian) network to represent features of the domain that are needed to identify users’ plans and...
David W. Albrecht, Ingrid Zukerman, Ann E. Nichols...
ICPR
2010
IEEE
13 years 5 months ago
Regression-Based Multi-view Facial Expression Recognition
We present a regression-based scheme for multi-view facial expression recognition based on 2-D geometric features. We address the problem by mapping facial points (e.g. mouth corn...
Ognjen Rudovic, Ioannis Patras, Maja Pantic
ICRA
2005
IEEE
138views Robotics» more  ICRA 2005»
14 years 1 months ago
Urban Object Recognition from Informative Local Features
Abstract— Autonomous mobile agents require object recognition for high level interpretation and localization in complex scenes. In urban environments, recognition of buildings mi...
Gerald Fritz, Christin Seifert, Lucas Paletta
DAGSTUHL
2006
13 years 9 months ago
Many-to-Many Feature Matching in Object Recognition
One of the bottlenecks of current recognition (and graph matching) systems is their assumption of one-to-one feature (node) correspondence. This assumption breaks down in the gener...
Ali Shokoufandeh, Yakov Keselman, M. Fatih Demirci...
PR
2010
147views more  PR 2010»
13 years 6 months ago
Minimum classification error learning for sequential data in the wavelet domain
Wavelet analysis has found widespread use in signal processing and many classification tasks. Nevertheless, its use in dynamic pattern recognition have been much more restricted ...
D. Tomassi, Diego H. Milone, L. Forzani