运动图像跟踪过程中丢帧误差消除技术

为解决传统方法不能自动对跟踪窗口的大小进行调整,造成跟踪定位误差高,无法有效消除丢帧误差的问题,提出一种新的运动图像跟踪过程中丢帧误差消除方法。通过对帧间差分法进行优化,利用每帧获取的背景部分完成背景模型的更新处理,通过当前帧和背景模型的差分获取运动范围。利用优化的Mean-shift法对运动图像进行跟踪处理,采用改进的帧差法对目标边缘进行提取,完成Mean-shift搜索窗口的更新处理,自适应调整跟踪窗口大小。通过适于P帧幅度能量模型对此刻帧与上一帧图像信息的改变程度进行描述,以体现运动图像序列运动分布情况,对运动图像跟踪中的丢帧误差情况进行描述。在此基础上求得运动图像跟踪状态矩阵,完成对丢帧状态参数的处理,将丢帧误差消除,以增强运动图像跟踪质量。结果表明,所提方法误差消除效果好,运动图像跟踪精度高。可见该方法能够对丢帧误差进行有效消除。

Research on eliminating frame error in moving image tracking

In order to solve the traditional method, the size of the tracking window cannot be automatically adjusted, resulting in high tracking error, and the problem of frame loss error cannot be effectively eliminated. A new method for eliminating frame error in moving image tracking is proposed. By optimizing the inter-frame difference method, the background model is processed by using the background portion acquired in each frame, and the motion range is obtained by the difference between the current frame and the background model. The moving image is tracked by the optimized Mean-shift method, and the target edge is extracted by the improved frame difference method. The update process of the Mean-shift search window is completed, and the tracking window size is adaptively adjusted. The degree of change of the image information of the frame and the previous frame is described by the P-frame amplitude energy model to reflect the motion distribution of the moving image sequence, and the frame loss error in the moving image tracking is described. On this basis, the moving image tracking state matrix is ??obtained, and the processing of the frame loss state parameters is completed, and the frame loss error is eliminated to enhance the moving image tracking quality. The results show that the proposed method has good error elimination effect and high accuracy of moving image tracking. It can be seen that the method can effectively eliminate the frame loss error.