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HRI
2007
ACM
14 years 2 months ago
Efficient model learning for dialog management
Intelligent planning algorithms such as the Partially Observable Markov Decision Process (POMDP) have succeeded in dialog management applications [10, 11, 12] because of their rob...
Finale Doshi, Nicholas Roy
ICCV
2009
IEEE
13 years 8 months ago
Efficient human pose estimation via parsing a tree structure based human model
Human pose estimation is the task of determining the states (location, orientation and scale) of each body part. It is important for many vision understanding applications, e.g. v...
Xiaoqin Zhang, Changcheng Li, Xiaofeng Tong, Weimi...
FGR
2006
IEEE
205views Biometrics» more  FGR 2006»
14 years 5 months ago
Tracking Using Dynamic Programming for Appearance-Based Sign Language Recognition
We present a novel tracking algorithm that uses dynamic programming to determine the path of target objects and that is able to track an arbitrary number of different objects. The...
Philippe Dreuw, Thomas Deselaers, David Rybach, Da...
CSL
2010
Springer
13 years 11 months ago
Bayesian update of dialogue state: A POMDP framework for spoken dialogue systems
This paper describes a statistically motivated framework for performing real-time dialogue state updates and policy learning in a spoken dialogue system. The framework is based on...
Blaise Thomson, Steve Young
IJRR
2011
218views more  IJRR 2011»
13 years 5 months ago
Motion planning under uncertainty for robotic tasks with long time horizons
Abstract Partially observable Markov decision processes (POMDPs) are a principled mathematical framework for planning under uncertainty, a crucial capability for reliable operation...
Hanna Kurniawati, Yanzhu Du, David Hsu, Wee Sun Le...