基于特征点的模板匹配车辆跟踪

Jong-Ho Choi, Kang-Ho Lee, Kuk-Chan Cha, Jun-Sik Kwon, Dong-Wook Kim, Ho-Keun Song
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引用次数: 17

摘要

本文提出了一种新的车辆跟踪系统,该系统可以检测和监控违反车道规则的车辆。我们提出的跟踪方案是基于交通场景和车辆的特征。这些包括:背景信息、本地位置和移动车辆的大小。采用四向轮廓跟踪方法获得车辆的初始尺寸和位置。通过结合帧差分操作,使物体轮廓对亮度变化不那么敏感。每辆车都可以用四个特征点来描述。通过相对于中心位置的最小距离方法估计模板区域。实验结果表明,从场景的每一帧中提取特征点可以提高车辆跟踪系统的效率。利用模板的匹配点对车辆区域进行调整,解决了之前的遮挡问题
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vehicle Tracking using Template Matching based on Feature Points
We propose a new vehicle tracking system which can detect and monitor vehicles as they break traffic lane rules. Our proposed tracking scheme is based on characteristics of both traffic scene and vehicle. These include: background information, local position, and the size of a moving vehicle. The initial size and position of the vehicle are obtained using a 4-directional contour tracking method. The object contour is made less sensitive to luminosity changes by incorporating a frame differencing operation. Each vehicle can be described with four feature points. The template region is estimated by means of a minimum distance approach with respect to center position. Our experimental results confirm that extraction of feature points from each frame of the scene improves the efficiency of vehicle tracking systems. Furthermore, adjustment of the vehicle region with matched points of template resolves the previous problem of occlusion
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