Abstract
In recent, the field of object vehicles detection in video is very interested and had became applicable with methods of deep learning and machine learning. The main objective for these applications is to display the targeted object from the videos. This field still facing low detection accuracy problems. The paper goal is to develop an approach able to classify vehicles in videos by using HOG features, Linear SVM classifier as machine learning method and YOLOv3 (You Only Look Once, Version 3) algorithm as deep learning method. In the present work, we used the two famous public datasets for vehicles detection from videos, which are KITTI and GTI datasets. The result of this study addresses the problems of vehicle detection and improved the accuracy of the training.
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