Title :
Intelligent Vehicle Detection and Tracking for Highway Driving
Author :
Xu, Wanxin ; Qiu, Meikang ; Chen, Zhi ; Su, Hai
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Kentucky, Lexington, KY, USA
Abstract :
Due to the increment of vehicles, the traffic jamming in cities becomes a serious challenge and the safety of people is threatened. Intelligent transportation system (ITS) and intelligent vehicles are critical to the efficiency of city transportation. In the area related with ITS and intelligent vehicles, moving vehicle detection and tracking are the most challenging problems. In this paper, we propose a framework for vehicle detection and tracking and make an in-depth research in key algorithms and techniques. We also conduct a serial of experiments on the basis of the existing results. Experimental results show that our proposed approach is feasible and effective for vehicle detection and tracking.
Keywords :
automated highways; road traffic; support vector machines; traffic engineering computing; transportation; city transportation efficiency; highway driving; intelligent transportation system; intelligent vehicle detection; intelligent vehicle tracking; support vector machine; traffic jamming; Equations; Feature extraction; Histograms; Mathematical model; Support vector machines; Target tracking; Vehicles; HOG Feature; Mean Shift; Part-based Model; SVM; Vehicle Detection; Vehicle Tracking;
Conference_Titel :
Multimedia and Expo Workshops (ICMEW), 2012 IEEE International Conference on
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4673-2027-6
DOI :
10.1109/ICMEW.2012.19