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Robust neural net based data association and multiple model based tracking of multiple point targets

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Title Robust neural net based data association and multiple model based tracking of multiple point targets
 
Creator ZAVERI, MA
DESAI, UB
MERCHANT, SN
 
Subject expectation-maximization algorithm
maximum-likelihood
maneuvering targets
em algorithm
pmht
expectation maximization
interacting multiple model
neural network
mixture probability density function
data association
 
Description Data association and model selection are important factors for tracking multiple targets in a dense clutter environment without using apriori information about the target dynamic. We propose a neural network based tracking algorithm, incorporating interacting multiple model to track both maneuvering and non-maneuvering targets simultaneously in the presence of dense clutter. For data association, we use the Expectation-Maximization (EM) algorithm and Hopfield network to evaluate assignment weights. All validated measurements are used to update the target state and hence, it avoids the uncertainty about the origin of the measurements. In the proposed approach the data association process is defined to incorporate multiple models for target dynamics and probability density, function (pdf) of an observed data given target state and measurement association, is treated as a mixture pdf. This allows to combine the likelihood of a measurement due to each model, and consequently, it is possible to track any arbitrary trajectory in the presence of dense clutter.
 
Publisher SPIE-INT SOC OPTICAL ENGINEERING
 
Date 2011-10-24T00:27:52Z
2011-12-15T09:11:20Z
2011-10-24T00:27:52Z
2011-12-15T09:11:20Z
2004
 
Type Proceedings Paper
 
Identifier IMAGE PROCESSING: ALGORITHMS AND SYSTEMS III,5298,337-348
0-8194-5201-7
0277-786X
http://dx.doi.org/10.1117/12.521177
http://dspace.library.iitb.ac.in/xmlui/handle/10054/15280
http://hdl.handle.net/100/2001
 
Source Conference on Image Processing - Algorithms and Systems III,San Jose, CA,JAN 19-21, 2004
 
Language English