Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/74309
Title: Vehicle detection in intelligent transportation systems and its applications under varying environments : a review
Authors: Yang, Z 
Pun-Cheng. LSC 
Keywords: Computer vision
Intelligent Transportation Systems
Traffic surveillance
Varying environments
Vehicle detection
Issue Date: 2017
Publisher: Elsevier
Source: Image and Vision Computing, 2017, p. 2 How to cite?
Journal: Image and Vision Computing 
Abstract: Robust and efficient vehicle detection in monocular vision is an important task in Intelligent Transportation Systems. With the development of computer vision techniques and consequent accessibility of video image data, new applications have been enabled to on-road vehicle detection algorithms. This paper provides a review of the literature in vehicle detection under varying environments. Due to the variability of on-road driving environments, vehicle detection may face different problems and challenges. Therefore, many approaches have been proposed, and can be categorized as appearance-based methods and motion-based methods. In addition, special illumination, weather and driving scenarios are discussed in terms of methodology and quantitative evaluation. In the future, efforts should be focused on robust vehicle detection approaches for various on-road conditions.
URI: http://hdl.handle.net/10397/74309
ISSN: 0262-8856
DOI: 10.1016/j.imavis.2017.09.008
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