Vehicle detection and classification in the Scala sensor by using binary classification

Minho Cho, Baehoon Choi, Jhonghyun An, Euntai Kim
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Abstract

In this paper, we present approach for the detection and classification of multiple vehicles using a vehicle mounted laser scanner. The sensor, which is placed in front of the vehicle, is Scala 1403 and its characteristic is that it scans data twice -upper and lower direction- in one period. Consequently, it is difficult to detect and classify vehicles continuously. For solving this problem, another method for classification is needed. In this paper, binary classification is proposed for classification of Scala sensor. It can show better classification result than by using SVM (support vector machine) in case of occlusions. Experimental results carried out with laser range data illustrate the robustness of our approach.
车辆检测与分类在Scala传感器中采用二值分类
在本文中,我们提出了一种使用车载激光扫描仪检测和分类多辆汽车的方法。放置在车辆前方的传感器是Scala 1403,它的特点是在一个周期内扫描两次数据——上下方向。因此,车辆的连续检测和分类是很困难的。为了解决这一问题,需要另一种分类方法。本文提出了对Scala传感器进行二值分类的方法。在遮挡情况下,该方法比支持向量机(SVM)分类效果更好。用激光测距数据进行的实验结果表明了该方法的鲁棒性。
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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