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» Competing Hidden Markov Models on the Self-Organizing Map
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IJCAI
1997
13 years 8 months ago
Learning Topological Maps with Weak Local Odometric Information
cal maps provide a useful abstraction for robotic navigation and planning. Although stochastic mapscan theoreticallybe learned using the Baum-Welch algorithm,without strong prior ...
Hagit Shatkay, Leslie Pack Kaelbling
ESANN
2007
13 years 9 months ago
Visualisation of tree-structured data through generative probabilistic modelling
We present a generative probabilistic model for the topographic mapping of tree structured data. The model is formulated as constrained mixture of hidden Markov tree models. A nat...
Nikolaos Gianniotis, Peter Tino
ICCV
2003
IEEE
14 years 25 days ago
Markov-Based Failure Prediction for Human Motion Analysis
This paper presents a new method of detecting and predicting motion tracking failures with applications in human motion and gait analysis. We define a tracking failure as an event...
Shiloh L. Dockstader, Nikita S. Imennov, A. Murat ...
CDC
2008
IEEE
125views Control Systems» more  CDC 2008»
14 years 2 months ago
Estimation of non-stationary Markov Chain transition models
— Many decision systems rely on a precisely known Markov Chain model to guarantee optimal performance, and this paper considers the online estimation of unknown, nonstationary Ma...
Luca F. Bertuccelli, Jonathan P. How
ICIP
2003
IEEE
14 years 9 months ago
Deformable face mapping for person identification
This paper introduces a novel deformable model for face mapping and its application to automatic person identification. While most face recognition techniques directly model the f...
Florent Perronnin, Jean-Luc Dugelay, Kenneth Rose