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Reseach Article

Implementation of Hybrid Model of Particle Filter and Kalman Filter based Real-Time Tracking for handling Occlusion on Beagleboard-xM

by Jharna Majumdar, Parashar Dhakal, Nabin Sharma Rijal, Amar Mani Aryal, Nilesh Kumar Mishra
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 95 - Number 7
Year of Publication: 2014
Authors: Jharna Majumdar, Parashar Dhakal, Nabin Sharma Rijal, Amar Mani Aryal, Nilesh Kumar Mishra
10.5120/16608-6443

Jharna Majumdar, Parashar Dhakal, Nabin Sharma Rijal, Amar Mani Aryal, Nilesh Kumar Mishra . Implementation of Hybrid Model of Particle Filter and Kalman Filter based Real-Time Tracking for handling Occlusion on Beagleboard-xM. International Journal of Computer Applications. 95, 7 ( June 2014), 31-37. DOI=10.5120/16608-6443

@article{ 10.5120/16608-6443,
author = { Jharna Majumdar, Parashar Dhakal, Nabin Sharma Rijal, Amar Mani Aryal, Nilesh Kumar Mishra },
title = { Implementation of Hybrid Model of Particle Filter and Kalman Filter based Real-Time Tracking for handling Occlusion on Beagleboard-xM },
journal = { International Journal of Computer Applications },
issue_date = { June 2014 },
volume = { 95 },
number = { 7 },
month = { June },
year = { 2014 },
issn = { 0975-8887 },
pages = { 31-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume95/number7/16608-6443/ },
doi = { 10.5120/16608-6443 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:18:50.575852+05:30
%A Jharna Majumdar
%A Parashar Dhakal
%A Nabin Sharma Rijal
%A Amar Mani Aryal
%A Nilesh Kumar Mishra
%T Implementation of Hybrid Model of Particle Filter and Kalman Filter based Real-Time Tracking for handling Occlusion on Beagleboard-xM
%J International Journal of Computer Applications
%@ 0975-8887
%V 95
%N 7
%P 31-37
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Particle filter is considered as one of the most robust and accurate techniques in object tracking because of its capability to handle non-linear and non-Gaussian problems. However this technique fails whenever the tracked object is occluded by other objects. In order to solve this problem, in this paper, we have proposed a computer vision based target tracking algorithm that combines both particle filter and Kalman filter. When the target is visible, particle filter is used for tracking the target but whenever there is occlusion, Kalman filter is used to predict and estimate the state of the occluded target. Hence, the proposed algorithm provides accurate results during both visible and occluded conditions. In order to verify the validity and effectiveness of the proposed algorithm, implementation on BeagleBoard-xM, an ARM based embedded platform, has been done. Integration of tracking algorithm on embedded platform paves the way for many real world applications like automated surveillance, human computer interaction, robotics, traffic monitoring etc.

References
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Index Terms

Computer Science
Information Sciences

Keywords

ARM BeagleBoard-xM Distance Measures Embedded Computer Vision Gstreamer Kalman Filter Particle filters Re-Sampling SDL Target Tracking.