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Title: Arbitrary trajectories tracking using multiple model based particle filtering in infrared image sequence
Authors: ZAVERI, MA
Keywords: Filtering Theory
Image Sequences
Infrared Imaging
Target Tracking
Issue Date: 2004
Publisher: IEEE
Citation: Proceedings of the International Conference on Information Technology:Coding and Computing (V 1), Las Vegas, Nevada, 5-7 April 2004, 603-607
Abstract: 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. In this paper we propose a novel method, which overcomes the above problem. In the 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. In the proposed approach, there is no need to have apriori information about the exact model that a target may follow.
URI: 10.1109/ITCC.2004.1286530
ISBN: 0-7695-2108-8
Appears in Collections:Proceedings papers

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