Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI | http://purl.tuc.gr/dl/dias/DFC1EFD4-9317-45F8-9CE6-33B425E8A4A7 | - |
| Identifier | https://doi.org/10.1109/TCSVT.2017.2711259 | - |
| Identifier | https://ieeexplore.ieee.org/document/7938384 | - |
| Language | en | - |
| Extent | 15 pages | en |
| Title | Data-driven background subtraction algorithm for in-camera acceleration in thermal imagery | en |
| Creator | Makantasis Konstantinos | en |
| Creator | Μακαντασης Κωνσταντινος | el |
| Creator | Nikitakis Antonios | en |
| Creator | Νικητακης Αντωνιος | el |
| Creator | Doulamis Anastasios | en |
| Creator | Δουλαμης Αναστασιος | el |
| Creator | Doulamis Nikolaos D. | en |
| Creator | Papaefstathiou Ioannis | en |
| Creator | Παπαευσταθιου Ιωαννης | el |
| Publisher | Institute of Electrical and Electronics Engineers | en |
| Content Summary | 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 |
| Type of Item | Peer-Reviewed Journal Publication | en |
| Type of Item | Δημοσίευση σε Περιοδικό με Κριτές | el |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2019-06-04 | - |
| Date of Publication | 2018 | - |
| Subject | Background subtraction | en |
| Subject | Foreground estimation | en |
| Subject | Thermal imaging | en |
| Subject | Variational inference | en |
| Bibliographic Citation | 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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