Moving vehicle detection and tracking using monocular vision Online publication date: Thu, 30-Oct-2014
by Xiaodong Miao; Shunming Li; Huan Shen; Hanquan Wang; Aijing Ma
International Journal of Vehicle Safety (IJVS), Vol. 7, No. 3/4, 2014
Abstract: This paper aims at real-time vehicle detection and tracking. It presents a novel comprehensive algorithm by multi-cues fusion in sequence images based on monocular vision. Firstly, the vertical symmetry of vehicle rear view is utilised to extract the Region of Interest (ROI) so as to narrow the search area. And then, the sign of underneath shadow is employed to generate hypothetical positions on which potential vehicles maybe present. Following, both image intensity and figure information are used to verify the vertical symmetry of the potential vehicle candidates. Meanwhile, Mean Shift, based on the object features' model of combine colour Histogram and Orientation Histogram (HOG), is employed to fast search the potential objects. More important, both detection and tracking are under an interactive mechanism which can dramatically improve detection efficiency. Experimental results show this approach can achieve 96.34% accurate rate and run on an average 24.27 frames per second, which satisfy the driving requirements.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Vehicle Safety (IJVS):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook