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Monocular vision-based range estimation of on-road vehicles

机译:基于单眼视觉的公路车辆测距

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This paper presents a monocular vision-based range estimation of on-road vehicles approach. The proposed approach mainly combines non-drivable region from drivable region detection for detection region estimation instead of detecting the whole image, shadow detection for on-road object extraction, vehicle structure points estimation and adjusting for on-road vehicle classification, and motion vector and Kalman filter of on-road vehicles for collision avoiding. Extensive experimentation was performed to demonstrate that the proposed approach can correctly and dynamically estimate the relative distance of on-road vehicles in actual traffic conditions.
机译:本文提出了一种基于单眼视觉的道路车辆行驶距离估计方法。所提出的方法主要将来自可驾驶区域检测的非可驾驶区域用于检测区域估计,而不是检测整个图像,用于道路物体提取的阴影检测,用于道路车辆分类的车辆结构点估计和调整,以及运动矢量和避免碰撞的公路车辆的卡尔曼滤波器。进行了广泛的实验,证明了该方法能够正确,动态地估计实际交通条件下公路车辆的相对距离。

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