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Data-driven background subtraction algorithm for in-camera acceleration in thermal imagery

Makantasis Konstantinos, Nikitakis Antonios, Doulamis Anastasios, Doulamis Nikolaos D., Papaefstathiou Ioannis

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URIhttp://purl.tuc.gr/dl/dias/DFC1EFD4-9317-45F8-9CE6-33B425E8A4A7-
Identifierhttps://doi.org/10.1109/TCSVT.2017.2711259-
Identifierhttps://ieeexplore.ieee.org/document/7938384-
Languageen-
Extent15 pagesen
TitleData-driven background subtraction algorithm for in-camera acceleration in thermal imageryen
CreatorMakantasis Konstantinosen
CreatorΜακαντασης Κωνσταντινοςel
CreatorNikitakis Antoniosen
CreatorΝικητακης Αντωνιοςel
CreatorDoulamis Anastasiosen
CreatorΔουλαμης Αναστασιοςel
CreatorDoulamis Nikolaos D.en
CreatorPapaefstathiou Ioannisen
CreatorΠαπαευσταθιου Ιωαννηςel
PublisherInstitute of Electrical and Electronics Engineersen
Content SummaryDetection of moving objects in videos is a crucial step toward successful surveillance and monitoring applications. A key component for such tasks is called background subtraction and tries to extract regions of interest from the image background for further processing or action. For this reason, its accuracy and real-time performance are of great significance. Although effective background subtraction methods have been proposed, only a few of them take into consideration the special characteristics of thermal imagery. In this paper, we propose a background subtraction scheme, which models the thermal responses of each pixel as a mixture of Gaussians with unknown number of components. Following a Bayesian approach, our method automatically estimates the mixture structure, while simultaneously it avoids over-/underfitting. The pixel density estimate is followed by an efficient and highly accurate updating mechanism, which permits our system to be automatically adapted to dynamically changing operation conditions. We propose a reference implementation of our method in reconfigurable hardware achieving both adequate performance and low-power consumption. Adopting a high-level synthesis design and demanding floating point arithmetic operations are mapped in reconfigurable hardware, demonstrating fast prototyping and on-field customization at the same time.en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2019-06-04-
Date of Publication2018-
SubjectBackground subtractionen
SubjectForeground estimationen
SubjectThermal imagingen
SubjectVariational inferenceen
Bibliographic CitationK. Makantasis, A. Nikitakis, A. D. Doulamis, N. D. Doulamis and I. Papaefstathiou, "Data-driven background subtraction algorithm for in-camera acceleration in thermal imagery," IEEE Trans. Circuits Syst. Video Technol., vol. 28, no. 9, pp. 2090-2104, Sept. 2018. doi: 10.1109/TCSVT.2017.2711259en

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