装有摄像头的车辆实时车位检测*

Timo Féret, Pramod Chandrashekhariah, N. Trujillo
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引用次数: 3

摘要

本文提出了一种基于摄像机的停车位标记检测方法,该方法使用安装在车辆上的环视摄像机。通过引入标记特定图像特征提取管道和新的滤波阶段,我们在针孔相机和鱼眼镜头相机中检测停车位标记,而无需使用计算密集型鸟瞰图变换。在将一组紧凑的图像特征投影到3D空间后,我们的定向霍夫变换明确地找到所需方向上停车位标记的左右边缘,这是标记检测和跟踪的基础。我们提出了一种新的技术,以连贯的方式检测和跟踪场景中的停车位,同时保留了整体停车场布局的结构及其时间一致性。我们的算法被设计用于在车辆中使用的低成本硬件上运行,并且在ARM cpu上以30fps的速度运行。我们在代表停车位真实场景的视频上验证了我们的算法,包括标记遮挡、退化和不同的天气条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-time Parking Slot Detection for Camera-equipped Vehicles*
This paper proposes a novel camera-based approach for parking slot detection with markings, using surround-view cameras mounted on vehicles. By introducing a pipeline of marking-specific image feature extraction and novel filtering stages, we detect parking slot markings in pinhole cameras as well as in cameras with fisheye lenses without using a computationally intensive bird-view transformation. After projecting a compact set of image features into 3D space, our orientation-specific Hough transform finds explicitly the left and right edges of the parking slot markings in desired orientations, which is the basis for marking detection and tracking. We present a novel technique to detect and track the parking slots in the scene in a coherent manner, that preserves the structure of the overall parking layout and its temporal consistency. Our algorithm is designed to run on low cost hardware used in vehicles and it is shown to run at 30fps on ARM CPUs. We validated our algorithm on videos representing real-world scenarios of parking slots including marking occlusion, degradation and different weather conditions.
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