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Vehicle Detection and Tracking at Night in Video Surveillance
Journal Title International Journal of Online Engineering (iJOE)
Journal Abbreviation i-joe
Publisher Group International Association of Online Engineering (IAOE)
Website http://online-journals.org
   
Title Vehicle Detection and Tracking at Night in Video Surveillance
Authors Tian, Qing; Zhang, Long; Wei, Yun; Zhao, Wenhua; Fei, Weiwei
Abstract This Many detection and tracking methods are able to detect and track vehicle motion reliably in the daytime. However, vehicle detection and tracking in video surveillance at night remain very important problems that the vehicle signatures have low contrast against the background. Traditional methods based on the analysis of the difference between successive frames and a background frame can not work. This paper presents a method for vehicle detection and tracking at night in video surveillance. The method uses Histograms of Oriented Gradients (HOG) features to extract features, and then uses Support Vector Machine (SVM) to recognize the object. In tracking phase, we use Kalman filter to track the object. As shown in experiments, the algorithm can exactly detect and track moving vehicles in video surveillance at night.
Publisher kassel university press GmbH
Date 2013-06-26
Source 1868-1646
Rights The submitting author warrants that the submission is original and that she/he is the author of the submission together with the named co-authors; to the extend the submission incorporates text passages, figures, data or other material from the work of others, the submitting author has obtained any necessary permission.
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