针对固定监控场景设计并实现了一个实时的运动目标检测与跟踪系统。在复杂背景下,改进的三帧差分法能准确、快速检测出运动目标。金字塔图像的LucasKanade光流法跟踪目标容易丢失;传统的模板匹配跟踪方法由于对图像利用率高,其跟踪比较准确,但计算量大。文章将两者结合起来,可以避免上述问题。实验表明,该算法能较好地实现目标跟踪、获得目标运动轨迹,且具有良好的实时性和鲁棒性。
A real-time moving object detection and tracking system aimed at fixed monitoring scene was designed and achieved. Improved three frames difference can detect moving object accurately and rapidly in a complex background. Tracking object will lose easily when using the Lucas-Kanade optical flow of pyramid image. The traditional template matching method can track the object much accurately because of high utilization rate of the image,but its amount of computation is too large. The algorithm in this paper can avoid above problems by integrating the two methods. The experiment shows that this algorithm can achieve tracking object better and gain the trajectory of moving object, which has good real-time performance and robustness.