Trends in Correlation-Based Pattern Recognition and Tracking in Forward-Looking Infrared Imagery

In this paper, we review the recent trends and advancements on correlation-based pattern recognition and tracking in forward-looking infrared (FLIR) imagery. In particular, we discuss matched filter-based correlation techniques for target detection and tracking which are widely used for various real...

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Detalles Bibliográficos
Autores principales: Alam, Mohammad S., Bhuiyan, Sharif M. A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2014
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4179048/
https://www.ncbi.nlm.nih.gov/pubmed/25061840
http://dx.doi.org/10.3390/s140813437
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author Alam, Mohammad S.
Bhuiyan, Sharif M. A.
author_facet Alam, Mohammad S.
Bhuiyan, Sharif M. A.
author_sort Alam, Mohammad S.
collection PubMed
description In this paper, we review the recent trends and advancements on correlation-based pattern recognition and tracking in forward-looking infrared (FLIR) imagery. In particular, we discuss matched filter-based correlation techniques for target detection and tracking which are widely used for various real time applications. We analyze and present test results involving recently reported matched filters such as the maximum average correlation height (MACH) filter and its variants, and distance classifier correlation filter (DCCF) and its variants. Test results are presented for both single/multiple target detection and tracking using various real-life FLIR image sequences.
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spelling pubmed-41790482014-10-02 Trends in Correlation-Based Pattern Recognition and Tracking in Forward-Looking Infrared Imagery Alam, Mohammad S. Bhuiyan, Sharif M. A. Sensors (Basel) Article In this paper, we review the recent trends and advancements on correlation-based pattern recognition and tracking in forward-looking infrared (FLIR) imagery. In particular, we discuss matched filter-based correlation techniques for target detection and tracking which are widely used for various real time applications. We analyze and present test results involving recently reported matched filters such as the maximum average correlation height (MACH) filter and its variants, and distance classifier correlation filter (DCCF) and its variants. Test results are presented for both single/multiple target detection and tracking using various real-life FLIR image sequences. MDPI 2014-07-24 /pmc/articles/PMC4179048/ /pubmed/25061840 http://dx.doi.org/10.3390/s140813437 Text en © 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Alam, Mohammad S.
Bhuiyan, Sharif M. A.
Trends in Correlation-Based Pattern Recognition and Tracking in Forward-Looking Infrared Imagery
title Trends in Correlation-Based Pattern Recognition and Tracking in Forward-Looking Infrared Imagery
title_full Trends in Correlation-Based Pattern Recognition and Tracking in Forward-Looking Infrared Imagery
title_fullStr Trends in Correlation-Based Pattern Recognition and Tracking in Forward-Looking Infrared Imagery
title_full_unstemmed Trends in Correlation-Based Pattern Recognition and Tracking in Forward-Looking Infrared Imagery
title_short Trends in Correlation-Based Pattern Recognition and Tracking in Forward-Looking Infrared Imagery
title_sort trends in correlation-based pattern recognition and tracking in forward-looking infrared imagery
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4179048/
https://www.ncbi.nlm.nih.gov/pubmed/25061840
http://dx.doi.org/10.3390/s140813437
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