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Automated model selection based algorithm for tracking multiple nonlinear trajectories

DSpace at IIT Bombay

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Title Automated model selection based algorithm for tracking multiple nonlinear trajectories
 
Creator ZAVERI, MA
DESAI, UB
MERCHANT, SN
 
Subject monte-carlo methods
multitarget tracking
target tracking
particle filtering
interacting multiple model
automated model selection
data association
 
Description Particle filtering is being investigated extensively due to its important feature of target tracking based on nonlinear and non-Gaussian model. It tracks a trajectory with a known model at a given time. It means that particle filter tracks an arbitrary trajectory only if the time instant when trajectory switches from one model to another model is known apriori. Because of this reason particle filter is not able to track any arbitrary trajectory where transition from one model to another model is not known. For real world application, trajectory is always random in nature and may follow more than one model. Another problem with multiple trajectories tracking using particle filter is the data association, i.e. observation to track fusion. In this paper we propose a novel method, which overcomes the above problems. In a proposed method an interacting multiple model based approach is used along with particle filtering, which automates the model selection process for tracking an arbitrary trajectory. We have utilized nearest neighbor (NN) method for data association, which is fast and easy to implement.
 
Publisher SPIE-INT SOC OPTICAL ENGINEERING
 
Date 2011-10-24T00:23:10Z
2011-12-15T09:11:20Z
2011-10-24T00:23:10Z
2011-12-15T09:11:20Z
2004
 
Type Proceedings Paper
 
Identifier IMAGE PROCESSING: ALGORITHMS AND SYSTEMS III,5298,242-250
0-8194-5201-7
0277-786X
http://dx.doi.org/10.1117/12.521174
http://dspace.library.iitb.ac.in/xmlui/handle/10054/15279
http://hdl.handle.net/100/2000
 
Source Conference on Image Processing - Algorithms and Systems III,San Jose, CA,JAN 19-21, 2004
 
Language English