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CVPR
2006
IEEE
15 years 11 months ago
Unsupervised Bayesian Detection of Independent Motion in Crowds
While crowds of various subjects may offer applicationspecific cues to detect individuals, we demonstrate that for the general case, motion itself contains more information than p...
Gabriel J. Brostow, Roberto Cipolla
ECCV
2006
Springer
15 years 11 months ago
Multivariate Relevance Vector Machines for Tracking
This paper presents a learning based approach to tracking articulated human body motion from a single camera. In order to address the problem of pose ambiguity, a one-to-many mappi...
Arasanathan Thayananthan, Ramanan Navaratnam, Bj&o...
BIOCOMP
2007
14 years 11 months ago
Interaction Models for Biochemical Reactions
Abstract—This paper presents a stochastic modelling framework for complex biochemical reaction networks from a component-based perspective. Our approach takes into account the di...
Mila E. Majster-Cederbaum, Nils Semmelrock, Verena...
105
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JAIR
2008
107views more  JAIR 2008»
14 years 9 months ago
Planning with Durative Actions in Stochastic Domains
Probabilistic planning problems are typically modeled as a Markov Decision Process (MDP). MDPs, while an otherwise expressive model, allow only for sequential, non-durative action...
Mausam, Daniel S. Weld
IJRR
2011
218views more  IJRR 2011»
14 years 4 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...