动态背景下基于运动矢量补偿的目标检测

在动态场景下，为了降低背景运动对目标检测产生误差的影响，针对视频序列图像，提出基于运动矢量 补偿的目标检测算法。采用背景运动补偿方法来完成目标检测，利用 SURF 特征点来获取精确的匹配点对，从而获 取准确的运动矢量；根据运动目标和背景运动矢量位移的不同来区分出前景和背景区域，将背景运动矢量代入模型 进行参数估计，提高背景补偿的精度；用帧差法检测出运动目标。实验结果表明：该算法具有鲁棒性，能够准确检 测出动态背景下的运动目标。

Object Detection Based on Motion Vector Compensation in Dynamic Background

In dynamic background, in order to reduce the influence of background motion on target detection, the paper proposed a target detection algorithm based on motion vector compensation for video sequence images. In this paper, background motion compensation method is used to complete target detection. Firstly, the accurate matching points are obtained by using SURF feature points, and the accurate motion vectors are obtained; Then, the foreground and the background areas are distinguished according to the displacement of the moving target and the background motion vector, the background motion vector are substituted into the model to estimate the parameters, which can improve the accuracy of the background compensation; Finally, the moving target is detected by frame difference method. The experimental results demonstrate that the algorithm is robust and can detect moving objects accurately in the dynamic background.