基于改进光流法的旋转运动背景下对地运动目标实时检测

针对战机对地侦查视频图像中地面旋转运动背景下运动目标检测高虚警、低实时性的问题,提出了一种基于改进光流法的旋转运动背景下对地运动目标实时检测算法。首先提取图像的特征点，在特征点处计算光流运动矢量，并通过光流矢量场估算背景运动矢量。根据战机飞行高度自适应计算目标像素尺寸，网格化分块待检测图像；然后将各个特征点光流矢量与背景运动矢量相比较，获得备选目标特征点。最后统计分块备选目标特征点密度，判断目标位置区域。对2组实验视频中央360像素×432像素区域进行目标检测实验，结果表明该算法能够准确地检测出地面运动目标，虚警率低。平均每帧检测耗时分别为29.460 ms和31.505 ms，满足战机对地运动目标检测的实时性。

Real Time Ground Moving Object Detection in Rotational

To solve the problem of high false alarm and low real time for aerial video with rotational ground background in moving object detection, a real time algorithm based on optical flow method is proposed. The image feature points are detected first, the optical flows are calculated, and the motion vector of the image background is estimated through optical flow field. Then the target size is calculated according to the flight height and the image is divided into blocks. Each feature point optical flow is compared with the motion vector of the image background to find out the candidates of the target feature point. Finally the candidates is added up in each block and the target areas are determined. Moving objects detection experiment is achieved for 360 pix×432 pix central area of two groups of experiment video. The result indicates that the algorithm can exactly detect the ground moving object with a low false alarm. The average consuming time is 29.460 ms/frame and 31.505 ms/frame, thus satisfying the real time requirements.