Visual Object Target Tracking Using Particle Filter: A Survey

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Author(s)

G. Mallikarjuna Rao 1,* Ch. Satyanarayana 2

1. DRDO (RCI), Andhra Pradesh, India

2. Department of Computer Science and Engineering Jawaharlal Nehru Technological University Kakinada. Andhra Pradesh, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2013.06.08

Received: 5 Feb. 2013 / Revised: 6 Mar. 2013 / Accepted: 11 Apr. 2013 / Published: 8 May 2013

Index Terms

Kalman Filter, Extended Kalman Filter, Unscented Kalman Filter, Particle Filter, Visual Object Tracking

Abstract

This paper gives the survey of the existing developments of Visual object target tracking using particle filter from the last decade and discusses the advantage and disadvantages of various particle filters. A variety of different approaches and algorithms have been proposed in literature. At present most of the work in Visual Object Target Tracking is focusing on using particle filter. The particle filters has the advantage that they deal with nonlinear models and non-Gaussian innovations, and they focus sequentially on the higher density regions of the state space, mostly parallelizable and easy to implement, so it gives a robust tracking framework, as it models the uncertainty and showing good improvement in the recognition performance compared to the kalman filter and other filters like Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF).Various features and classifiers that are used with particle filter are given in this survey.

Cite This Paper

G.Mallikarjuna Rao,Ch.Satyanarayana,"Visual Object Target Tracking Using Particle Filter: A Survey", IJIGSP, vol.5, no.6, pp.57-71, 2013. DOI: 10.5815/ijigsp.2013.06.08

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