Training method for vehicle detection

M. Kang, Y. Lim
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Abstract

Recently, vehicle detection methods have been popularly used in the field of intelligent vehicles. The performance and processing time of vehicle detection is very important because it is associated with the life of a driver. However, all vehicle detection methods generate missing detections and false detections because of different vehicle appearances. However, in a general road environment, the appearance of most of these vehicles has a front and a rear. In this paper, we propose a training method to detect the front and rear of the vehicle. Our vehicle detection integrates state-of-the-art feature-based detection.
车辆检测训练方法
近年来,车辆检测方法在智能汽车领域得到了广泛的应用。车辆检测的性能和处理时间是非常重要的,因为它关系到驾驶员的生命。然而,由于车辆外观的不同,所有的车辆检测方法都会产生缺失检测和错误检测。然而,在一般的道路环境中,这些车辆的外观大多有一个前和一个后。在本文中,我们提出了一种训练方法来检测车辆的前后。我们的车辆检测集成了最先进的基于特征的检测。
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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