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3D road curb extraction from image sequence for automobile parking assist system

机译:汽车停车辅助系统从图像序列中提取3D道路路缘

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We extract 3D curb from video sequence, using a single camera equipped with fish-eye lens and located at the front/rear of the vehicle. The challenge in extracting curbs from images lies in their small size and their lack of texture. We show that by appropriately exploiting appearance features, 3D geometry, and temporal information, one can reliably detect and localize the curbs in the 3D scene. The main underlying assumption of our model is that the road surface is flat and that the curb is approximately orthogonal to the road plane. We collected nine videos with ground truth, under day-time sunny weather condition, up to 2m range. Our experimental results compare favorably wrt the current the state-of-the-art on our database —90% precision rate in average and over 85% accuracy in curb height estimation.
机译:我们使用配备了鱼眼镜头且位于车辆前/后方的单个摄像头,从视频序列中提取3D遏制。从图像中提取路缘石的挑战在于它们的小尺寸和缺乏纹理。我们表明,通过适当利用外观特征,3D几何形状和时间信息,人们可以可靠地检测和定位3D场景中的路边石。我们模型的主要基本假设是路面平坦,路缘与路面近似正交。在白天晴天的情况下,我们收集了9个具有地面真实性的视频,范围最大为2m。我们的实验结果与数据库上的最新技术相比具有可比性-平均准确率达90%,路缘高度估算准确率达85%以上。

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