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Recognizing the Illegal Parking Patterns of Cars on the Road in Front of the Bus Stop Using the Support Vector Machine

机译:使用支持向量机认识到公交车前面的道路上的汽车的非法停车模式

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Traffic jams are a major problem in the lives of people in the capital. The occurrence of such problems is due to drivers who do not respect traffic laws, inappropriate behavior of the driver, and the cause of illegal parking at prohibited parking, resulting in the rear car unable to move further. Possible or the car must change lanes to another lane. Therefore, to reduce such problems, we have developed an illegal parking pattern recognition system for cars on the road. We have applied the Support Vector Machine (SVM) to the signal from CCTV cameras and find important characteristics of illegal car parked at the bus stop. Then use those images to learn to recognize the parking behavior of cars with Linear Regression. From the experiment, it is found that the recognition of cars parked on the road in front of the bus stop has an accuracy rate of 82.22 percent which can be used to detect the soaking of personal cars in real life.
机译:交通堵塞是资本人民生活中的一个主要问题。这种问题的发生是由于驾驶员不尊重交通法律,驾驶员的不当行为以及禁止停车处的非法停车的原因,导致后车无法进一步移动。可能或汽车必须将车道换成另一门车道。因此,为了减少此类问题,我们已经为道路上的汽车制定了非法停车模式识别系统。我们已经将支持向量机(SVM)应用于CCTV摄像机的信号,并找到了在巴士站停放的非法车的重要特征。然后使用这些图像学习以线性回归识别汽车的停车行为。从实验中,发现识别停放在公交车站前面的道路上的汽车的准确率为82.22%,可用于检测现实生活中的个人汽车的浸泡。

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