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A Real-Time System for Detecting Illegal Changes-of-Lane Based on Tracking of Feature Points

机译:基于特征点跟踪的非法车道变化实时检测系统

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This paper proposes a real time system for detecting vehicles that change lanes illegally based on tracking the feature points. The proposed system consists of three stages, which take part of the roles such as feature extraction of corners, registration and tracking the feature points attached to vehicles, and detecting a vehicle that violates legal lane changes. In the stage of feature extraction, we used a fast algorithm that can provide stable corners. The salient points are again selected among the corner points for registration and tracking. NCC(normalized cross correlation) is used to keep tracing the registered feature points. Finally, illegal change-of-lane is detected by the information about the traced corners. As a result of experiment, the proposed system showed excellent performance as amount of 99.09% of correct detection ratio and 0.9% of error. The fast processing could deal with 34.48 frames per second, which is sufficient for real-time processing.
机译:本文提出了一种基于特征点跟踪的实时检测违章行驶车辆的实时系统。拟议的系统包括三个阶段,其中包括角色的提取,拐角的特征提取,配准和跟踪附加到车辆上的特征点以及检测违反合法车道变更的车辆等角色。在特征提取阶段,我们使用了可以提供稳定拐角的快速算法。再次从拐角点中选择突出点,以进行配准和跟踪。 NCC(归一化互相关)用于保持跟踪注册的特征点。最终,通过关于所跟踪拐角的信息检测到非法的车道改变。实验结果表明,所提出的系统具有良好的性能,正确检出率为99.09%,错误检出率为0.9%。快速处理可以每秒处理34.48帧,这足以进行实时处理。

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