Efficient Multitarget Visual Tracking Using Random Finite Sets

We propose a filtering framework for multitarget tracking that is based on the probability hypothesis density (PHD) filter and data association using graph matching. This framework can be combined with any object detectors that generate positional and dimensional information of objects of interest....

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Bibliographic Details
Published in:	IEEE transactions on circuits and systems for video technology Vol. 18; no. 8; pp. 1016 - 1027
Main Authors:	Maggio, E., Taj, M., Cavallaro, A.
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.08.2008 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Bayesian methods Detectors Filtering Layout Matched filters Monte Carlo Nonlinear filters Object detection Particle filters probability hypothesis density (PHD) filter Studies surveillance Target tracking tracking Video surveillance Surveillance Monte Carlo tracking PHD filter
ISSN:	1051-8215, 1558-2205
Online Access:	Get full text
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