Abstract
With the rapid development of technologies, road traffic surveillance tends to be more intelligent. Detection of
non-public vehicles driving in public bus lanes is one of the emerging applications. Commonly, fixed cameras are
adopted in video surveillance systems. Compared with the limited monitoring areas of fixed cameras, mobile cameras
can follow the moving targets and in this way greatly extend the monitoring areas. However, for mobile cameras, many
detection methods do not perform well because the background is rapidly changing and the target is moving fast as well.
In this paper, we propose a novel method to detect non-public vehicles driving in the bus lanes (hence violating the
traffic regulations) using mobile cameras installed on buses. In particular, we first use Hough transform and SVM
classifier with color features to detect bus lanes, and then use AdaBoost cascade classifier with Haar features to detect
license plates in the bus lane area. Finally another SVM classifier is used to classify the color of the license plate to
determine if it belongs to a non-public vehicle. As shown in the experiments, our method is proven to be robust to
complex background and performs well in the real world situations.
