Ιδρυματικό Αποθετήριο
Πολυτεχνείο Κρήτης
Πολυτεχνείο Κρήτης
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| URI | http://purl.tuc.gr/dl/dias/DFC1EFD4-9317-45F8-9CE6-33B425E8A4A7 | - |
| Αναγνωριστικό | https://doi.org/10.1109/TCSVT.2017.2711259 | - |
| Αναγνωριστικό | https://ieeexplore.ieee.org/document/7938384 | - |
| Γλώσσα | en | - |
| Μέγεθος | 15 pages | en |
| Τίτλος | Data-driven background subtraction algorithm for in-camera acceleration in thermal imagery | en |
| Δημιουργός | Makantasis Konstantinos | en |
| Δημιουργός | Μακαντασης Κωνσταντινος | el |
| Δημιουργός | Nikitakis Antonios | en |
| Δημιουργός | Νικητακης Αντωνιος | el |
| Δημιουργός | Doulamis Anastasios | en |
| Δημιουργός | Δουλαμης Αναστασιος | el |
| Δημιουργός | Doulamis Nikolaos D. | en |
| Δημιουργός | Papaefstathiou Ioannis | en |
| Δημιουργός | Παπαευσταθιου Ιωαννης | el |
| Εκδότης | Institute of Electrical and Electronics Engineers | en |
| Περίληψη | Detection 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 |
| Τύπος | Peer-Reviewed Journal Publication | en |
| Τύπος | Δημοσίευση σε Περιοδικό με Κριτές | el |
| Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
| Ημερομηνία | 2019-06-04 | - |
| Ημερομηνία Δημοσίευσης | 2018 | - |
| Θεματική Κατηγορία | Background subtraction | en |
| Θεματική Κατηγορία | Foreground estimation | en |
| Θεματική Κατηγορία | Thermal imaging | en |
| Θεματική Κατηγορία | Variational inference | en |
| Βιβλιογραφική Αναφορά | K. 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.2017.2711259 | en |
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