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» Learning from Multiple Annotators with Gaussian Processes
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ECAI
2006
Springer
15 years 3 months ago
Least Squares SVM for Least Squares TD Learning
Abstract. We formulate the problem of least squares temporal difference learning (LSTD) in the framework of least squares SVM (LS-SVM). To cope with the large amount (and possible ...
Tobias Jung, Daniel Polani
ICIP
2007
IEEE
16 years 1 months ago
3D Human Motion Tracking using Manifold Learning
This paper introduces a framework to track 3D human movement using Gaussian process dynamic model (GPDM) and particle filter. The framework combines the particle filter and discri...
Feng Guo, Gang Qian
UAI
2004
15 years 1 months ago
Dynamical Systems Trees
We propose dynamical systems trees (DSTs) as a flexible model for describing multiple processes that interact via a hierarchy of aggregating processes. DSTs extend nonlinear dynam...
Andrew Howard, Tony Jebara
ICIAP
2001
Springer
15 years 12 months ago
Recognition of Shape-Changing Hand Gestures Based on Switching Linear Model
We present a method to track and recognize shape-changing hand gestures simultaneously. The switching linear model using active contour model well corresponds to temporal shapes a...
Mun Ho Jeong, Yoshinori Kuno, Nobutaka Shimada, Yo...
ICCV
2007
IEEE
15 years 6 months ago
Action Recognition from Arbitrary Views using 3D Exemplars
In this paper, we address the problem of learning compact, view-independent, realistic 3D models of human actions recorded with multiple cameras, for the purpose of recognizing th...
Daniel Weinland, Edmond Boyer, Rémi Ronfard