移动摄像视频的多运动目标实时跟踪算法

Real Time Multiple Moving Targets Tracking Algorithm of Video by Moving Camera

针对运动摄像头视频序列多运动目标检测准确率与实时性较差的问题,提出一种新的多运动目标检测与追踪算法。首先,使用Harris角点提高运动像素检测的准确率,将角点作为特征点提高特征点分类的准确率;设计了前景特征点更新方法与基于透视变换的背景特征点提取方法进一步提高分类性能,并且设计了自运动补偿与细化算法减小运动摄像头的影响;最终,采用基于最小外接矩形框引力中心的Kalman滤波器实现多运动目标的追踪。仿真实验结果表明,此方法对快速多运动目标的追踪具有较好的性能,同时具有较好的实时性。

Aimed at the problem that the existing multiple moving target tracking algorithms of video by moving cameras have poor performance in accuracy, a new real time multiple moving targets detection and tracking algorithm is proposed. Firstly, Harris corner is used to improve the accuracy of moving pixel detection, corners are set as feature points to improve the accuracy of classification; then, the foreground feature point updating method and perspective transformation based background feature point abstraction method are designed to improve the classification performance, and motion compensation and refinement methods are designed to reduce the influence of moving cameras; lastly, minimum bounding box gravity center based Kalman filter is used to realize multiple moving target tracking. Simulation experiment results show that the proposal has better performance in fast multiple moving target tracking and also is real time.