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Rearview Camera-Based Stixel Generation for Backing Crash Prevention

机译:基于后视摄像头的Stixel生成可防止后备碰撞

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摘要

Backing crashes have become a serious problem, resulting in the United States announcing a rule requiring all vehicles to come equipped with rearview cameras. As a result of this situation, this paper proposes a method that detects obstacles behind a vehicle using a rearview camera with a fisheye lens. The proposed method represents obstacles by means of the Stixel World, and it consists of two stages: free space boundary detection and obstacle height estimation. In the first stage, obstacles are three-dimensionally reconstructed, and the 3D points are spatially interpolated and sequentially accumulated. An occupancy grid map is generated with depth and incidence angle axes to effectively handle a wide field-of-view situation. In the second stage, this method combines some complementary information to reliably estimate the obstacle height using spare 3D points. Three cost maps based on 3D points, color similarity, and edge strength are calculated and fused in height and incidence angle axes. The free space boundary and the obstacle height are estimated by finding the optimal paths in the occupancy grid map and the fused cost map, respectively. Finally, Stixels are generated by integrating the free space boundary and obstacle height. In the experiment, the proposed method was quantitatively evaluated and compared with the previous methods in various road, obstacle, and background conditions.
机译:倒车事故已经成为一个严重的问题,导致美国宣布一项规定,要求所有车辆必须配备后视摄像头。作为这种情况的结果,本文提出了一种使用带有鱼眼镜头的后视摄像机检测车辆后方障碍物的方法。所提出的方法通过Stixel World来表示障碍物,它包括两个阶段:自由空间边界检测和障碍物高度估计。在第一阶段,对障碍物进行三维重构,然后对3D点进行空间插值并顺序累积。使用深度和入射角轴生成占用栅格图,以有效处理宽视野范围的情况。在第二阶段,此方法结合了一些补充信息,以使用备用3D点可靠地估计障碍物高度。基于3D点,颜色相似度和边缘强度的三个成本图被计算并融合在高度和入射角轴上。通过分别在占用网格图和融合成本图中找到最佳路径来估计自由空间边界和障碍物高度。最后,通过合并自由空间边界和障碍物高度来生成Stixel。在实验中,对提出的方法进行了定量评估,并在各种道路,障碍物和背景条件下与以前的方法进行了比较。

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