基于视觉传达的后继帧视频图像目标跟踪仿真

现阶段所采用的跟踪方法对后继帧视频图像目标跟踪存在跟踪效果不理想、跟踪效率较低等问题。提出基于视觉传达的后继帧视频图像目标跟踪方法。利用图像差分方法获取视频图像运动目标可能出现的区域,并对这个区域视频图像目标进行运动估计,采用形态学方法来降低聚类区域的数量,得到后继帧视频图像目标区域;采用均值漂移法估计后继帧视图像核概率密度,对后继帧视频图像进行分割处理,找出后继帧视频图像目标区域最显著的特征,通过迭代运算找到目标位置,实现目标跟踪。实验结果表明,所提算法具有较好的后继帧视频图像跟踪效果、并且跟踪效率较高,具有一定的应用价值。

Target Tracking Simulation of Subsequent Frame Video Image Based on Visual Communication

At present, the tracking method leads to unsatisfactory tracking effect and low tracking efficiency. In this article, a target tracking method for subsequent frame video images based on visual communication was presented. At first, we used the image difference method to get the possible regions of video image moving targets, and performed the motion estimation on targets in this region. Then, we used morphological method to reduce the number of clustering regions, so as to obtain the target region of subsequent frame video image. Moreover, we used the mean shift method to estimate the kernel probability density of subsequent frame video image, and split the video image, so as to find out the most striking feature of the target area. Finally, we used the iterative operation to find target location and thus to achieve the target tracking. Simulation results show that the proposed algorithm has better tracking effect and higher tracking efficiency of subsequent frame video image.