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Traffic flow detection based on scene knowledge

机译:基于场景知识的交通流检测

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摘要

Traffic flow detection is the advanced stage in the intelligence surveillance. In this paper, we first parameterize the scene knowledge (as lane etc.) using Radon transform and Polynomial fitting to boundary of road. The features of Hu moment were used for tracking the moving objects; the scene knowledge and the fictitious coil were cited for analyzing the traffic flow of moving objects. The experimental results show that our algorithms are effectives.
机译:交通流检测是智能监控的高级阶段。在本文中,我们首先使用Radon变换和对道路边界的多项式拟合来参数化场景知识(例如车道等)。胡矩的特征被用来跟踪运动物体。引用了场景知识和虚拟线圈来分析运动物体的交通流。实验结果表明我们的算法是有效的。

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