基于AdaBoost和类Haar特征的监控视频运动车辆检测
Moving Vehicle Detection Using AdaBoost and Haar-Like Feature in Surveillance Videos
摘要：
车辆检测是一种在数字图像中定位并显示车辆大小的技术。在这项技术中，车辆在树木和建筑物等其他物体的存在下被检测到。它在车辆跟踪、交通场景分析、高效交通管理等计算机视觉应用中具有重要作用。本文基于Viola Jones提出的Boosting技术对车辆进行检测。我们提出的系统进行了测试，在不同的光照条件下的监控视频的一些真实场景。实验结果表明，所提出的车辆检测方法的准确性，完整性和质量优于以前的技术（约94%，92%和87%，分别）。因此，我们提出的方法是强大的和有效的检测车辆监控视频及其应用。
英文摘要：
Vehicle detection is a technology which its aim is to locate and show the vehicle size in digital images. In this technology, vehicles are detected in presence of other things like trees and buildings. It has an important role in many computer vision applications such as vehicle tracking, analyzing the traffic scene and efficient traffic management. In this paper, vehicles detected based on the boosting technique by Viola Jones. Our proposed system is tested in some real scenes of surveillance videos with different light conditions. The experimental results show that the accuracy,completeness, and quality of the proposed vehicle detection method are better than the previous techniques (about 94%, 92%, and 87%, respectively). Thus, our proposed approach is robust and efficient to detect vehicles in surveillance videos and their applications.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
