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A Warning System for Obstacle Detection at Vehicle Lateral Blind Spot Area

机译:车辆侧盲区的障碍物检测预警系统

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摘要

For a real driver assistance system, the weather, driving speed, and background could affect the accuracy of obstacle detection. In the past, only a few studies covered all the different weather conditions and almost none of them had paid attention to the safety at vehicle lateral blind spot area. So, this paper proposes a hybrid scheme for pedestrian and vehicle detection, and develop a warning system dedicated for lateral blind spot area under different weather conditions and driving speeds. More specifically, the HOG and SVM methods are used for pedestrian detection. The image subtraction, edge detection and tire detection are applied for vehicle detection. Experimental results also show that the proposed system can efficiently detect pedestrian and vehicle under several scenarios.
机译:对于真正的驾驶员辅助系统,天气,行驶速度和背景可能会影响障碍物检测的准确性。过去,只有很少的研究涵盖了所有不同的天气条件,并且几乎没有研究关注车辆侧向盲区的安全性。因此,本文提出了一种行人和车辆检测的混合方案,并开发了一种专用于在不同天气条件和行驶速度下侧向盲区的预警系统。更具体地说,HOG和SVM方法用于行人检测。图像减法,边缘检测和轮胎检测被应用于车辆检测。实验结果还表明,所提出的系统可以在多种情况下有效地检测行人和车辆。

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