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Frequency-Tuned Taillight-Based Nighttime Vehicle Braking Warning System

机译:基于频率调整的基于尾灯的夜间车辆制动警告系统

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摘要

Advanced vehicle safety is a critical issue in recent years for automobiles, especially when the number of vehicles is growing rapidly worldwide. The decreasing cost of cameras makes it feasible to have an intelligent system of visually based event detection in front for forward collision avoidance and mitigation. When driving at night, vehicles in front are generally visible by their taillights. The brake lights are particularly important because drivers need to focus on them. Therefore, in this paper, we propose a novel approach that can detect brake lights at night using a camera by analyzing the signal in both spatial and frequency domains. Unlike the traditional approaches that employ the knowledge of the heuristic features, such as symmetry and position of rear facing vehicle, size, and so on, we focus on finding the invariant features from the regions of brake lights in the frequency domain and therefore can conduct the detection process in a part-based manner. Experiments with an extensive dataset show that our proposed system can efficiently and effectively detect brake lights under different lighting and traffic conditions, and thus prove its feasibility in real-world environments.
机译:先进的车辆安全性是近年来汽车的关键问题,尤其是在全球范围内车辆数量迅速增长的情况下。摄像机成本的降低使得在前方拥有一个基于视觉的事件检测智能系统来避免和减轻前向碰撞成为可能。在夜间驾驶时,通常可以通过尾灯看到前方的车辆。刹车灯特别重要,因为驾驶员需要专注于刹车灯。因此,在本文中,我们提出了一种新颖的方法,该方法可以通过在空间和频域中分析信号来使用相机在夜间检测刹车灯。与采用启发式特征(例如,后向车辆的对称性和位置,尺寸等)的知识的传统方法不同,我们专注于从频域中的制动灯区域中找到不变特征,因此可以进行基于零件的检测过程。通过大量数据集的实验表明,我们提出的系统可以在不同的照明和交通条件下有效地检测刹车灯,从而证明其在现实环境中的可行性。

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