Visual Target Detection and Tracking Based on Kalman Filter

In this study, in order to prevent collision and target tracking in autonomous aircraft, Kalman filter with appropriate solutions for target detection and tracking problems are presented. For the Kalman filter application, the motion-based tracking method that facilitates the tracking of multiple ob...

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Main Author: Gülay ÜNAL
Format: Article
Language:English
Published: Turkish Air Force Academy 2021-07-01
Series:Havacılık ve Uzay Teknolojileri Dergisi
Subjects:
Online Access:http://jast.hho.edu.tr/index.php/JAST/article/view/475
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author Gülay ÜNAL
author_facet Gülay ÜNAL
author_sort Gülay ÜNAL
collection DOAJ
description In this study, in order to prevent collision and target tracking in autonomous aircraft, Kalman filter with appropriate solutions for target detection and tracking problems are presented. For the Kalman filter application, the motion-based tracking method that facilitates the tracking of multiple objects has been used. A background subtraction algorithm was used for the detection of moving objects while corrective actions were applied to the foreground mask to eliminate noise, and the connected pixel groups correspond to moving objects were identified. The used image represents an image taken by a hovering drone. Although the tracked multiple targets disappeared behind the obstacle, the estimated location was determined by means of Kalman filter. Thanks to the fine tuning of the program codes, a successful follow-up has been achieved. The program has continued to follow the moving shadow as a part of the target.
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spelling doaj.art-5f201c2d9bc047389e4db877b514aebc2023-02-15T16:20:24ZengTurkish Air Force AcademyHavacılık ve Uzay Teknolojileri Dergisi1304-04481304-04482021-07-01142251259Visual Target Detection and Tracking Based on Kalman FilterGülay ÜNAL0https://orcid.org/0000-0001-8285-0954Eskisehir Technical UniversityIn this study, in order to prevent collision and target tracking in autonomous aircraft, Kalman filter with appropriate solutions for target detection and tracking problems are presented. For the Kalman filter application, the motion-based tracking method that facilitates the tracking of multiple objects has been used. A background subtraction algorithm was used for the detection of moving objects while corrective actions were applied to the foreground mask to eliminate noise, and the connected pixel groups correspond to moving objects were identified. The used image represents an image taken by a hovering drone. Although the tracked multiple targets disappeared behind the obstacle, the estimated location was determined by means of Kalman filter. Thanks to the fine tuning of the program codes, a successful follow-up has been achieved. The program has continued to follow the moving shadow as a part of the target.http://jast.hho.edu.tr/index.php/JAST/article/view/475target trackingkalman filtertarget detection.
spellingShingle Gülay ÜNAL
Visual Target Detection and Tracking Based on Kalman Filter
Havacılık ve Uzay Teknolojileri Dergisi
target tracking
kalman filter
target detection.
title Visual Target Detection and Tracking Based on Kalman Filter
title_full Visual Target Detection and Tracking Based on Kalman Filter
title_fullStr Visual Target Detection and Tracking Based on Kalman Filter
title_full_unstemmed Visual Target Detection and Tracking Based on Kalman Filter
title_short Visual Target Detection and Tracking Based on Kalman Filter
title_sort visual target detection and tracking based on kalman filter
topic target tracking
kalman filter
target detection.
url http://jast.hho.edu.tr/index.php/JAST/article/view/475
work_keys_str_mv AT gulayunal visualtargetdetectionandtrackingbasedonkalmanfilter