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A Combined PMHT and IMM Approach to Multiple-Point Target Tracking in Infrared Image Sequence

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Title A Combined PMHT and IMM Approach to Multiple-Point Target Tracking in Infrared Image Sequence
 
Creator ZAVERI, MA
MERCHANT, SN
DESAI, UB
 
Description Data association and model selection are important factors for tracking multiple targets in a dense clutter environment. In this paper, we provide an effective solution to the tracking of multiple single-pixel maneuvering targets in a sequence of infrared images by developing an algorithm that combines a sequential probabilistic multiple hypothesis tracking (PMHT) and interacting multiple model (IMM). We explicitly model maneuver as a change in the target's motion model and demonstrate its effectiveness in our tracking application discussed in this paper. We show that inclusion of IMM enables tracking of any arbitrary trajectory in a sequence of infrared images without any a priori special information about the target dynamics. IMM allows us to incorporate different dynamic models for the targets and PMHT helps to avoid the uncertainty about the observation origin. It operates in an iterative mode using expectation-maximization (EM) algorithm. The proposed algorithm uses observation association as missing data. Copyright (C) 2007 .
 
Publisher HINDAWI PUBLISHING CORPORATION
 
Date 2011-07-31T07:02:44Z
2011-12-26T12:52:52Z
2011-12-27T05:39:50Z
2011-07-31T07:02:44Z
2011-12-26T12:52:52Z
2011-12-27T05:39:50Z
2007
 
Type Article
 
Identifier EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING, (), -
1687-5176
http://dx.doi.org/10.1155/2007/19139
http://dspace.library.iitb.ac.in/xmlui/handle/10054/8023
http://hdl.handle.net/10054/8023
 
Language en