Tracking of multiple-point targets using multiple-model-based particle filtering in infrared image sequence

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Tracking of multiple-point targets using multiple-model-based particle filtering in infrared image sequence

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Title: Tracking of multiple-point targets using multiple-model-based particle filtering in infrared image sequence
Author: ZAVERI, MA; MERCHANT, SN; DESAI, UB
Abstract: Particle filtering is investigated extensively due to its importance in target tracking for nonlinear and non-Gaussian models. A particle filter can track an arbitrary trajectory only if the target dynamics models are known and the time instant when trajectory switches from one model to another model is known a priori. In real applications, it is unlikely to meet both these conditions. We propose a novel method that overcomes the lack of this knowledge. In the proposed method, an interacting multiple-model-based approach is exploited along with particle filtering. Moreover, we automate the model selection process for tracking an arbitrary trajectory. In the proposed approach, a priori information about the exact model that a target may follow is not required. Another problem with multiple trajectory tracking using a particle filter is data association, namely, observation to track fusion. For data association, we use three methods. In the first case, an implicit observation to track assignment is performed using a nearest neighbor (NN) method for data association; this is fast and easy to implement. In the second method, the uncertainty about the origin of an observation is overcome by using a centroid of measurements to evaluate weights for particles as well as to calculate the likelihood of a model. In the third method, a Markov random field (MRF)-based method is used. The MRF method enables us to exploit the neighborhood concept for data association, i.e., the association of a measurement influences an association of its neighboring measurement. (C) 2006 Society of Photo-Optical Instrumentation Engineers.
URI: http://dx.doi.org/10.1117/1.2205858
http://dspace.library.iitb.ac.in/xmlui/handle/10054/12019
http://hdl.handle.net/10054/12019
Date: 2006


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