运动估计在ADAS中的应用

Muhammad Hannan Fathi bin Rasdi, N. Hashim, S. Hanizam
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引用次数: 0

摘要

环视监控(AVM)系统使用多个摄像头作为传感器,安装在车辆的多个位置上,以显示车辆周围环境的俯视图图像,由于驾驶员的视野有限,驾驶员不易看到这些图像。通过开发能够监测周边区域、检测车位、车道和障碍物的系统,可以降低停车事故发生的风险。几秒钟的早期预警将大大减少事故发生的几率。该系统可以在停车区域和狭窄的空间区域提供辅助导航。目前可用的AVM通常需要另一个传感器来确保良好的性能输出。但这不仅会增加计算时间和资源,而且还会增加成本。本文提出了一种与运动估计算法相结合的AVM系统,以获得较好的效果。AVM图像序列来自安装在车辆上的摄像机输入。要测试的算法是加纳·法内巴克。检测连续帧中的运动并将其转换为真实世界的位置变化。本文将对不同情况下的算法进行比较。测量了结果的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Around View Monitoring System with Motion Estimation in ADAS Application
Around View Monitoring (AVM) system uses multiple cameras as the sensor that is mounted on several positions on the vehicle to produce a display of top view image from the surrounding environment of the vehicle that is not readily visible to the driver because of the limited field of view of the driver. The risk of parking accident could be reduced by developing the system that can monitor the surrounding area, detecting parking slot lane and obstacle. A few seconds of early warning would significantly decrease the chances of accidents. This system can assist in the parking area and navigating through a narrow space area. Current AVM available usually needed another sensor to ensure a good performance output. But this is cost consuming besides increasing the computational time and resource. Here, proposed an AVM system that will integrate with the motion estimation algorithm to produce a good result. The AVM image sequence is from a camera input mounted on the vehicle. The algorithm to be tested is Gunnar Farneback. Movement in sequential frames is detected and converted to the real-world position change. This paper will compare the algorithms in various condition. The accuracy of the result was measured.
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