571 search results - page 46 / 115 » Learning to Track with Multiple Observers |
ICIP
2008
IEEE
14 years 2 months ago
2008
IEEE
In this paper, we introduce a new method for tracking multiple objects. The method combines Kalman filtering and the Expectation Maximization (EM) algorithm in a novel way to dea...
EVENT
2001
13 years 9 months ago
2001
Determining the occurrence of an event is fundamental to developing systems that can observe and react to them. Often, this determination is based on collecting video and/or audio...
AROBOTS
2011
13 years 2 months ago
2011
Abstract— GP-BayesFilters are a general framework for integrating Gaussian process prediction and observation models into Bayesian filtering techniques, including particle filt...
NIPS
2004
13 years 9 months ago
2004
Multiple realizations of continuous-valued time series from a stochastic process often contain systematic variations in rate and amplitude. To leverage the information contained i...
ICCV
2009
IEEE
13 years 5 months ago
2009
IEEE
In this paper, we propose a unified graphical-model framework to interpret a scene composed of multiple objects in monocular video sequences. Using a single pairwise Markov random...