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

Zhejiang Shuren University ,H Chen,A Nedzvedz,S Ye,Belarusian State University ,S Ablameyko,Belarusian State Medical University ,O Nedzvedz,United Institute Of Informatics Problems Of National Academy Of Sciences ,H Lv

doi:10.18287/2412-6179-2019-43-4-647-652

Zhejiang Shuren University , H Chen + Show 8 more

Open Access

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

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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.

Highlights

Traffic flow monitoring and analysis based on computer vision techniques, especially traffic analysis and monitoring in a real-time mode raise valuable and complicated demands to computer algorithms and technological solutions
Traffic analysis on urban traffic domain appears to be more challenging because of high-density traffic flow and low camera angle that lead to a high degree of occlusion (Rodríguez and García [4])
Our paper is devoted to important problem of traffic analysis by stationary camera and detection of complex situations that can appear on roads

Summary

Introduction

Traffic flow monitoring and analysis based on computer vision techniques, especially traffic analysis and monitoring in a real-time mode raise valuable and complicated demands to computer algorithms and technological solutions. A road monitoring system based upon image analysis must detect and react to a changing scene This adaptability can be brought about by a generalized approach to the problem which incorporates little or no a priori knowledge of the analyzed scene. Such a system should be able to detect ‘changing circumstances’, which may include non-standard situations like traffic jam, rapid cars accumulation and cars divergence in road intersections (Joshi and Mishra [8], Nagaraj et al [9], Shafie et al [10], Khanke and Kulkarni [11]). We applied our method on realword videos and got good results

Technology of car traffic monitoring by using motion maps

Integral optical flow and image motion maps

Definition and identification of cars movement types

Cars movement parameters calculation

Car flow monitoring results

Conclusion