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Computer Optics, 2019, Volume 43, Issue 4, Pages 647–652 (Mi co688)  

IMAGE PROCESSING, PATTERN RECOGNITION

Traffic extreme situations detection in video sequences based on integral optical flow

H. Chena, Sh. Yea, A. Nedzvedzbc, O. Nedzvedzd, H. Lva, S. V. Ablameykobc

a Zhejiang Shuren University, Hangzhou, China
b Belarusian State University, Minsk, Belarus
c United Institute of Informatics Problems of National Academy of Sciences, Minsk, Belarus
d Belarusian State Medical University, Minsk, Belarus

Abstract: Road traffic analysis is an important task in many applications and it can be used in video surveillance systems to prevent many undesirable events. In this paper, we propose a new method based on integral optical flow to analyze cars movement in video and detect flow extreme situations in real-world videos. Firstly, integral optical flow is calculated for video sequences based on optical flow, thus random background motion is eliminated; secondly, pixel-level motion maps which describe cars movement from different perspectives are created based on integral optical flow; thirdly, region-level indicators are defined and calculated; finally, threshold segmentation is used to identify different cars movements. We also define and calculate several parameters of moving car flow including direction, speed, density, and intensity without detecting and counting cars. Experimental results show that our method can identify cars directional movement, cars divergence and cars accumulation effectively.

Keywords: integral optical flow, image processing, road traffic control, video surveillance.

Funding Agency Grant Number
Zhejiang Provincial Natural Science Foundation of China LZ15F020001
Program of Zhejiang Province LGF19F020016
Program of Zhejiang Province LGJ18F020001
Program of Zhejiang Province LGJ19F020002
National High-end Foreign Experts Program GDW20183300463
The work was funded by Public Welfare Technology Applied Research Program of Zhejiang Province (LGF19F020016, LGJ18F020001 and LGJ19F020002), Zhejiang Provincial Natural Science Foundation of China (LZ15F020001), and the National High-end Foreign Experts Program (GDW20183300463).


DOI: https://doi.org/10.18287/2412-6179-2019-43-4-647-652

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Full text: http://www.computeroptics.smr.ru/.../430417.html
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Received: 14.01.2019
Accepted:18.04.2019

Citation: H. Chen, Sh. Ye, A. Nedzvedz, O. Nedzvedz, H. Lv, S. V. Ablameyko, “Traffic extreme situations detection in video sequences based on integral optical flow”, Computer Optics, 43:4 (2019), 647–652

Citation in format AMSBIB
\Bibitem{CheYeNed19}
\by H.~Chen, Sh.~Ye, A.~Nedzvedz, O.~Nedzvedz, H.~Lv, S.~V.~Ablameyko
\paper Traffic extreme situations detection in video sequences based on integral optical flow
\jour Computer Optics
\yr 2019
\vol 43
\issue 4
\pages 647--652
\mathnet{http://mi.mathnet.ru/co688}
\crossref{https://doi.org/10.18287/2412-6179-2019-43-4-647-652}


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