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» Learning Models for Object Recognition
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FGR
2004
IEEE
135views Biometrics» more  FGR 2004»
15 years 7 months ago
Bayesian Fusion of Hidden Markov Models for Understanding Bimanual Movements
Understanding hand and body gestures is a part of a wide spectrum of current research in computer vision and Human-Computer Interaction. A part of this can be the recognition of m...
Atid Shamaie, Alistair Sutherland
NAACL
2010
15 years 1 months ago
Unsupervised Model Adaptation using Information-Theoretic Criterion
In this paper we propose a novel general framework for unsupervised model adaptation. Our method is based on entropy which has been used previously as a regularizer in semi-superv...
Ariya Rastrow, Frederick Jelinek, Abhinav Sethy, B...
CORR
2012
Springer
198views Education» more  CORR 2012»
13 years 11 months ago
Lipschitz Parametrization of Probabilistic Graphical Models
We show that the log-likelihood of several probabilistic graphical models is Lipschitz continuous with respect to the ￿p-norm of the parameters. We discuss several implications ...
Jean Honorio
ACII
2007
Springer
15 years 7 months ago
Learning to Interact with the Caretaker: A Developmental Approach
To build autonomous robots able to live and interact with humans in a real-world dynamic and uncertain environment, the design of architectures permitting robots to develop attachm...
Antoine Hiolle, Lola Cañamero, Arnaud J. Bl...
131
Voted
ICRA
2009
IEEE
173views Robotics» more  ICRA 2009»
15 years 10 months ago
Most salient region tracking
— In this paper, we introduce a cognitive approach for object tracking from a mobile platform. The approach is based on a biologically motivated attention system which is able to...
Simone Frintrop, Markus Kessel