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» Discrete Approximations to Continuous Curves
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JMLR
2010
157views more  JMLR 2010»
13 years 2 months ago
Why are DBNs sparse?
Real stochastic processes operating in continuous time can be modeled by sets of stochastic differential equations. On the other hand, several popular model families, including hi...
Shaunak Chatterjee, Stuart Russell
ICIP
2003
IEEE
14 years 20 days ago
Shape metrics, warping and statistics
We propose to use approximations of shape metrics, such as the Hausdorff distance, to define similarity measures between shapes. Our approximations being continuous and different...
Guillaume Charpiat, Olivier D. Faugeras, Renaud Ke...
DGCI
2006
Springer
13 years 11 months ago
Improving Difference Operators by Local Feature Detection
Differential operators are required to compute several characteristics for continuous surfaces, as e.g. tangents, curvature, flatness, shape descriptors. We propose to replace diff...
Kristof Teelen, Peter Veelaert
CORR
2012
Springer
235views Education» more  CORR 2012»
12 years 3 months ago
An Incremental Sampling-based Algorithm for Stochastic Optimal Control
Abstract— In this paper, we consider a class of continuoustime, continuous-space stochastic optimal control problems. Building upon recent advances in Markov chain approximation ...
Vu Anh Huynh, Sertac Karaman, Emilio Frazzoli
CVPR
1999
IEEE
14 years 9 months ago
Time-Series Classification Using Mixed-State Dynamic Bayesian Networks
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...