Real-time vehicle detector with dynamic segmentation and rule-based tracking reasoning for complex traffic conditions

Bing-Fei Wu*, Jhy Hong Juang

*Corresponding author for this work

研究成果: Article

5 引文 斯高帕斯(Scopus)

摘要

Vision-based vehicle detector systems are becoming increasingly important in ITS applications. Real-time operation, robustness, precision, accurate estimation of traffic parameters, and ease of setup are important features to be considered in developing such systems. Further, accurate vehicle detection is difficult in varied complex traffic environments. These environments include changes in weather as well as challenging traffic conditions, such as shadow effects and jams. To meet real-time requirements, the proposed system first applies a color background to extract moving objects, which are then tracked by considering their relative distances and directions. To achieve robustness and precision, the color background is regularly updated by the proposed algorithm to overcome luminance variations. This paper also proposes a scheme of feedback compensation to resolve background convergence errors, which occur when vehicles temporarily park on the roadside while the background image is being converged. Next, vehicle occlusion is resolved using the proposed prior split approach and through reasoning for rule-based tracking. This approach can automatically detect straight lanes. Following this step, trajectories are applied to derive traffic parameters; finally, to facilitate easy setup, we propose a means to automate the setting of the system parameters. Experimental results show that the system can operate well under various complex traffic conditions in real time.

原文English
頁(從 - 到)2355-2373
頁數19
期刊KSII Transactions on Internet and Information Systems
5
發行號12
DOIs
出版狀態Published - 31 十二月 2011

指紋 深入研究「Real-time vehicle detector with dynamic segmentation and rule-based tracking reasoning for complex traffic conditions」主題。共同形成了獨特的指紋。

引用此