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Object Tracking Algorithm Based on Meanshift Algorithm Combining with Motion Vector Analysis

机译:基于均值漂移算法与运动矢量分析相结合的目标跟踪算法

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Mean shift algorithm doesn't use the targetpsilas motion direction and speed information in process of object tracking. When the targetpsilas speed is so fast it easily fails to track the target. So a new object tracking algorithm combining Mean shift algorithm with Motion Vector analysis is proposed in this paper. By statistical analysis of the motion vector get from video encoding process, we can get the motion direction and velocity of target, which can be used to correct the central point of the motion candidate region of Mean shift, making the search position is more close to the actual centre of the target. This method can not only track the fast moving target effectively, but also reduce the number of iterative convergence times to improve the efficiency of operations. The algorithm is already use in our intelligent video surveillance equipment in which the operation of video encoding and object tracking is executed in one chip, and the experimental results show that it is feasible and effective.
机译:均值平移算法在目标跟踪过程中不使用目标运动方向和速度信息。当靶标速度如此之快时,它很容易无法跟踪目标。为此,提出了一种将均值漂移算法与运动矢量分析相结合的目标跟踪算法。通过对视频编码过程中得到的运动矢量的统计分析,可以得到目标的运动方向和速度,可以用来校正均值漂移候选运动区域的中心点,使搜索位置更接近目标的实际中心。该方法不仅可以有效地跟踪快速移动的目标,而且可以减少迭代收敛次数,从而提高了运算效率。该算法已经在我们的智能视频监控设备中使用,该算法在一个芯片中执行视频编码和目标跟踪操作,实验结果表明该算法是可行和有效的。

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