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Please use this identifier to cite or link to this item: http://dspace.library.iitb.ac.in/jspui/handle/100/1996

Title: Interacting multiple model based tracking of multiple point targets using expectation maximization algorithm in infrared image sequence
Authors: ZAVERI, MA
DESAI, UB
MERCHANT, SN
Keywords: maximum-likelihood
maneuvering targets
incomplete data
em algorithm
pmht
Issue Date: 2003
Publisher: SPIE-INT SOC OPTICAL ENGINEERING
Citation: VISUAL COMMUNICATIONS AND IMAGE PROCESSING 2003, PTS 1-3,5150,303-314
Abstract: 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 Interacting Multiple Model-Expectation Maximization (IMM-EM) algorithm, by incorporating different dynamic models for the target and Markov Random Field (MRF) for data association, and hence it is possible to track maneuvering and non-maneuvering targets simultaneously in a single batch mode (sequential). Moreover it can be used for real time application. The proposed method overcomes the problem of data association by incooperating all validated measurements together using EM algorithm and exploiting MRF. It treats the data association problem as incomplete data problem. In the proposed method, all validated measurements are used to update the target state. It uses only measurement association as missing data, which simplifies E-step and M-step of the algorithm. In the proposed approach probability density function (pdf) of an observed data given target state and measurement association, is treated as a mixture pdf. This allows to combine likelihood of a measurement due to each model, and the association process is defined to incorporate IMM and consequently, it is possible to track any arbitrary trajectory. We also consider two different cases for association of measurement to target: Case I:-association of each measurement to target is independent of each other, Case II:- association of a measurement influences an association of its neighbor measurement.
URI: http://dx.doi.org/10.1117/12.499230
http://dspace.library.iitb.ac.in/xmlui/handle/10054/15276
http://hdl.handle.net/100/1996
ISBN: 0-8194-5023-5
ISSN: 0277-786X
Appears in Collections:Proceedings papers

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