Paper
27 October 2013 Non-public vehicle traffic-violation detection using mobile cameras
Huini Fu, Yang Hu, Rui Huang
Author Affiliations +
Proceedings Volume 8919, MIPPR 2013: Pattern Recognition and Computer Vision; 89190S (2013) https://doi.org/10.1117/12.2031350
Event: Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, 2013, Wuhan, China
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.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Huini Fu, Yang Hu, and Rui Huang "Non-public vehicle traffic-violation detection using mobile cameras", Proc. SPIE 8919, MIPPR 2013: Pattern Recognition and Computer Vision, 89190S (27 October 2013); https://doi.org/10.1117/12.2031350
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Cited by 1 scholarly publication.
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KEYWORDS
Cameras

Target detection

Video

Hough transforms

Video surveillance

Detection and tracking algorithms

Image processing

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