Traffic Flow Detection for Complex Scene Based on Image Sequence
Na Li, Jinqiao Feng, Jingshan Pan, Weidong Gu, Yanling Zhao, Guangqi Liu, Hongjun Zhong
Available Online March 2014.
- https://doi.org/10.2991/mce-14.2014.13How to use a DOI?
- vehicle detection; statistics of vehicle flow; complex scenes; background difference method; frame difference method
- A method of traffic flow detection for complex scenes based on image sequence is proposed, which is aiming at realizing intelligent vehicle detection and flow statistics for traffic videos shot by single camera located at the urban traffic intersection. For target vehicle detection, Gaussian-filtering mean method is utilized to create the dynamic real-time background; meanwhile it is combined with frame difference method to locate the motion vehicles in the foreground. Moreover, test-stripe detecting method is used for vehicle counting, in which data streams representing vehicle information are extracted with sliding window and are modified by Predictor-Corrector scheme to count the vehicles more accurately. Finally, a prototype system is designed to realize vehicle flow statistics for complex traffic scenes, combined with the judgment algorithm of vehicle traveling direction. Experimental simulation represents that target vehicle detection avoids the respective disadvantages of the two methods, that is background difference method and frame difference method, and obtains better detection effects. The prototype system captures good real-time performance and statistical data of the vehicle flow are comparatively accurate.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Na Li AU - Jinqiao Feng AU - Jingshan Pan AU - Weidong Gu AU - Yanling Zhao AU - Guangqi Liu AU - Hongjun Zhong PY - 2014/03 DA - 2014/03 TI - Traffic Flow Detection for Complex Scene Based on Image Sequence BT - 2014 International Conference on Mechatronics, Control and Electronic Engineering (MCE-14) PB - Atlantis Press SP - 58 EP - 64 SN - 1951-6851 UR - https://doi.org/10.2991/mce-14.2014.13 DO - https://doi.org/10.2991/mce-14.2014.13 ID - Li2014/03 ER -