The detecting and tracking system for vehicles

Chien-Chung Wu, Kai Weng
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引用次数: 6

Abstract

It's very important to monitor the surroundings while driving the car. This paper uses camera to detect the location of vehicles and that assists drivers in driving more safely through the alerting system. Meanwhile, there were two different algorithms tested in the vehicle detection system, including Haar with Adaboost, and HOG-PCA with SVM methods. The preliminary results of this paper have been able to successfully detect vehicle and track vehicle location. In the vehicle detection, the average precision rate of 39.77% has raised to 82.45%. The vehicle tracking section has presented an improved version of the particle filter. Furthermore, take 200 particles for the test, vehicles could be tracked accurately in and out of the tunnel in the dramatic changes of light.
车辆检测与跟踪系统
开车时监测周围环境是非常重要的。本文利用摄像头检测车辆的位置,并通过报警系统帮助驾驶员更安全的驾驶。同时,在车辆检测系统中测试了两种不同的算法,分别是采用Adaboost的Haar算法和采用SVM方法的HOG-PCA算法。本文的初步结果已经能够成功地检测车辆并跟踪车辆位置。在车辆检测中,平均准确率由39.77%提高到82.45%。车辆跟踪部分提出了粒子滤波的改进版本。此外,采用200个粒子进行测试,可以在光线剧烈变化的情况下准确跟踪车辆进出隧道。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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