IEICE TRANSACTIONS on Fundamentals
Real-Time UHD Background Modelling with Mixed Selection Block Updates
Summary :
The vast majority of foreground detection methods require heavy hardware optimization to process in real-time standard definition videos. Indeed, those methods process the whole frame for the detection but also for the background modelling part which makes them resource-guzzlers (time, memory, etc.) unable to be applied to Ultra High Definition (UHD) videos. This paper presents a real-time background modelling method called Mixed Block Background Modelling (MBBM). It is a spatio-temporal approach which updates the background model by carefully selecting block by a linear and pseudo-random orders and update the corresponding model's block parts. The two block selection orders make sure that every block will be updated. For foreground detection purposes, the method is combined with a foreground detection designed for UHD videos such as the Adaptive Block-Propagative Background Subtraction method. Experimental results show that the proposed MBBM can process 50min. of 4K UHD videos in less than 6 hours. while other methods are estimated to take from 8 days to more than 21 years. Compared to 10 state-of-the-art foreground detection methods, the proposed MBBM shows the best quality results with an average global quality score of 0.597 (1 being the maximum) on a dataset of 4K UHDTV sequences containing various situation like illumination variation. Finally, the processing time per pixel of the MBBM is the lowest of all compared methods with an average of 3.18×10-8s.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E100-A No.2 pp.581-591
- Publication Date
- 2017/02/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E100.A.581
- Type of Manuscript
- Special Section PAPER (Special Section on Image Media Quality)
- Category
- IMAGE PROCESSING
Authors
Axel BEAUGENDRE
Waseda University
Satoshi GOTO
Waseda University
Takeshi YOSHIMURA
Waseda University
Keyword
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Axel BEAUGENDRE, Satoshi GOTO, Takeshi YOSHIMURA, "Real-Time UHD Background Modelling with Mixed Selection Block Updates" in IEICE TRANSACTIONS on Fundamentals,
vol. E100-A, no. 2, pp. 581-591, February 2017, doi: 10.1587/transfun.E100.A.581.
Abstract: The vast majority of foreground detection methods require heavy hardware optimization to process in real-time standard definition videos. Indeed, those methods process the whole frame for the detection but also for the background modelling part which makes them resource-guzzlers (time, memory, etc.) unable to be applied to Ultra High Definition (UHD) videos. This paper presents a real-time background modelling method called Mixed Block Background Modelling (MBBM). It is a spatio-temporal approach which updates the background model by carefully selecting block by a linear and pseudo-random orders and update the corresponding model's block parts. The two block selection orders make sure that every block will be updated. For foreground detection purposes, the method is combined with a foreground detection designed for UHD videos such as the Adaptive Block-Propagative Background Subtraction method. Experimental results show that the proposed MBBM can process 50min. of 4K UHD videos in less than 6 hours. while other methods are estimated to take from 8 days to more than 21 years. Compared to 10 state-of-the-art foreground detection methods, the proposed MBBM shows the best quality results with an average global quality score of 0.597 (1 being the maximum) on a dataset of 4K UHDTV sequences containing various situation like illumination variation. Finally, the processing time per pixel of the MBBM is the lowest of all compared methods with an average of 3.18×10-8s.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E100.A.581/_p
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@ARTICLE{e100-a_2_581,
author={Axel BEAUGENDRE, Satoshi GOTO, Takeshi YOSHIMURA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Real-Time UHD Background Modelling with Mixed Selection Block Updates},
year={2017},
volume={E100-A},
number={2},
pages={581-591},
abstract={The vast majority of foreground detection methods require heavy hardware optimization to process in real-time standard definition videos. Indeed, those methods process the whole frame for the detection but also for the background modelling part which makes them resource-guzzlers (time, memory, etc.) unable to be applied to Ultra High Definition (UHD) videos. This paper presents a real-time background modelling method called Mixed Block Background Modelling (MBBM). It is a spatio-temporal approach which updates the background model by carefully selecting block by a linear and pseudo-random orders and update the corresponding model's block parts. The two block selection orders make sure that every block will be updated. For foreground detection purposes, the method is combined with a foreground detection designed for UHD videos such as the Adaptive Block-Propagative Background Subtraction method. Experimental results show that the proposed MBBM can process 50min. of 4K UHD videos in less than 6 hours. while other methods are estimated to take from 8 days to more than 21 years. Compared to 10 state-of-the-art foreground detection methods, the proposed MBBM shows the best quality results with an average global quality score of 0.597 (1 being the maximum) on a dataset of 4K UHDTV sequences containing various situation like illumination variation. Finally, the processing time per pixel of the MBBM is the lowest of all compared methods with an average of 3.18×10-8s.},
keywords={},
doi={10.1587/transfun.E100.A.581},
ISSN={1745-1337},
month={February},}
Copy
TY - JOUR
TI - Real-Time UHD Background Modelling with Mixed Selection Block Updates
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 581
EP - 591
AU - Axel BEAUGENDRE
AU - Satoshi GOTO
AU - Takeshi YOSHIMURA
PY - 2017
DO - 10.1587/transfun.E100.A.581
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E100-A
IS - 2
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - February 2017
AB - The vast majority of foreground detection methods require heavy hardware optimization to process in real-time standard definition videos. Indeed, those methods process the whole frame for the detection but also for the background modelling part which makes them resource-guzzlers (time, memory, etc.) unable to be applied to Ultra High Definition (UHD) videos. This paper presents a real-time background modelling method called Mixed Block Background Modelling (MBBM). It is a spatio-temporal approach which updates the background model by carefully selecting block by a linear and pseudo-random orders and update the corresponding model's block parts. The two block selection orders make sure that every block will be updated. For foreground detection purposes, the method is combined with a foreground detection designed for UHD videos such as the Adaptive Block-Propagative Background Subtraction method. Experimental results show that the proposed MBBM can process 50min. of 4K UHD videos in less than 6 hours. while other methods are estimated to take from 8 days to more than 21 years. Compared to 10 state-of-the-art foreground detection methods, the proposed MBBM shows the best quality results with an average global quality score of 0.597 (1 being the maximum) on a dataset of 4K UHDTV sequences containing various situation like illumination variation. Finally, the processing time per pixel of the MBBM is the lowest of all compared methods with an average of 3.18×10-8s.
ER -
English
