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Improvement of a Traffic Sign Detector by Retrospective Gathering of Training Samples from In-Vehicle Camera Image Sequences

机译:通过回顾性收集车载摄像机图像序列中的训练样本来改进交通标志检测器

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摘要

This paper proposes a method for constructing an accurate traffic sign detector by retrospectively obtaining training samples from in-vehicle camera image sequences. To detect distant traffic signs from in-vehicle camera images, training samples of distant traffic signs are needed. However, since their sizes are too small, it is difficult to obtain them either automatically or manually. When driving a vehicle in a real environment, the distance between a traffic sign and the vehicle shortens gradually, and proportionally, the size of the traffic sign becomes larger. A large traffic sign is comparatively easy to detect automatically. Therefore, the proposed method automatically detects a large traffic sign, and then small traffic signs (distant traffic signs) are obtained by retrospectively tracking it back in the image sequence. By also using the retrospectively obtained traffic sign images as training samples, the proposed method constructs an accurate traffic sign detector automatically. From experiments using in-vehicle camera images, we confirmed that the proposed method could construct an accurate traffic sign detector.
机译:本文提出了一种通过从车载摄像机图像序列中追溯获取训练样本来构造精确交通标志检测器的方法。为了从车载摄像机图像中检测远处的交通标志,需要训练远处的交通标志的样本。但是,由于它们的尺寸太小,很难自动或手动获得它们。当在真实环境中驾驶车辆时,交通标志与车辆之间的距离逐渐缩短,并且交通标志的尺寸成比例地变大。较大的交通标志比较容易自动检测。因此,所提出的方法自动检测到较大的交通标志,然后通过在图像序列中追溯性地回溯来获得较小的交通标志(远处的交通标志)。通过将回顾性获得的交通标志图像也用作训练样本,该方法自动构造了一个准确的交通标志检测器。从使用车载摄像机图像进行的实验中,我们证实了该方法可以构建一个准确的交通标志检测器。

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