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ML
2002
ACM
246views Machine Learning» more  ML 2002»
13 years 10 months ago
Bayesian Clustering by Dynamics
This paper introduces a Bayesian method for clustering dynamic processes. The method models dynamics as Markov chains and then applies an agglomerative clustering procedure to disc...
Marco Ramoni, Paola Sebastiani, Paul R. Cohen
PSIVT
2007
Springer
129views Multimedia» more  PSIVT 2007»
14 years 4 months ago
Multi-target Tracking with Poisson Processes Observations
This paper considers the problem of Bayesian inference in dynamical models with time-varying dimension. These models have been studied in the context of multiple target tracking pr...
Sergio Hernández, Paul Teal
EUROSSC
2006
Springer
14 years 2 months ago
Dynamic Bayesian Networks for Visual Surveillance with Distributed Cameras
Abstract. This paper presents a surveillance system for tracking multiple people through a wide area with sparsely distributed cameras. The computational core of the system is an a...
Wojciech Zajdel, Ali Taylan Cemgil, Ben J. A. Kr&o...
CVPR
2010
IEEE
14 years 6 months ago
What's going on? Discovering Spatio-Temporal Dependencies in Dynamic Scenes
We present two novel methods to automatically learn spatio-temporal dependencies of moving agents in complex dynamic scenes. They allow to discover temporal rules, such as the rig...
Daniel Kuettel, Michael Breitenstein, Luc Van Gool...
GECCO
2007
Springer
148views Optimization» more  GECCO 2007»
14 years 4 months ago
Exploring the behavior of building blocks for multi-objective variation operator design using predator-prey dynamics
In this paper, we utilize a predator-prey model in order to identify characteristics of single-objective variation operators in the multi-objective problem domain. In detail, we a...
Christian Grimme, Joachim Lepping, Alexander Papas...