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Vehicle detection and inter-vehicle distance estimation using single-lens video camera on urban/suburb roads

机译:在城市/郊区道路上使用单镜头摄像机进行车辆检测和车辆之间的距离估计

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This paper presents a driver assistance system for vehicle detection and inter-vehicle distance estimation using a single-lens video camera on urban/suburb roads. The task of vehicle detection on urban/suburb roads is more challenging due to their high scene complexity. In this work, the still area of frame inside the host vehicle is first removed using temporal differencing, followed by detecting vanishing point. Segmentation of road regions is then conducted using vanishing point and road's edge lines. Shadow regions at the bottoms of vehicles verified using the HOG feature and an SVM classifier are utilized to detect vehicle positions. The distances between the host and its front vehicles are estimated based on the locations of detected vehicles and vanishing point. Experimental results show varied performance of vehicle detection with different scenes of urban/suburb roads and the detection rate can achieve up to 94.08%, indicating the feasibility of the proposed method. (C) 2017 Elsevier Inc. All rights reserved.
机译:本文提出了一种在城市/郊区道路上使用单镜头摄像机进行车辆检测和车距估计的驾驶员辅助系统。由于城市/郊区道路的场景复杂性高,车辆检测任务更具挑战性。在这项工作中,首先使用时间差移除主车辆内部车架的静止区域,然后检测消失点。然后使用消失点和道路边缘线进行道路区域分割。使用HOG功能和SVM分类器验证的车辆底部阴影区域可用于检测车辆位置。根据检测到的车辆的位置和消失点来估算主机与其前部车辆之间的距离。实验结果表明,在不同的城市/郊区道路场景下,车辆检测性能各不相同,检测率可达94.08%,说明了该方法的可行性。 (C)2017 Elsevier Inc.保留所有权利。

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