This paper proposes a Mean Shift tracking method for fusion image.
提出一种针对融合图像的均值位移跟踪方法。
In the color image sequence, the mean shift algorithm is an efficient method for tracking object.
在彩色序列图像目标跟踪中，均值移位算法是一种有效的方法。
Mean shift is an effective iterative algorithm widely used in clustering, tracking, segmentation, discontinuity preserving smoothing, filtering, edge detection, and information fusion etc.
均值平移是一种有效的统计迭代算法，已广泛应用于聚类分析、跟踪、图像分割、图像平滑、滤波、图像边缘提取和信息融合等方面。
Recently, a hybrid tracker, seamlessly integrating the respective advantages of mean shift and particle filter (MSPF) has achieved impressive success in robust tracking.
近来，一种结合了均值偏移和粒子滤波各自优点的混合跟踪器取得了稳健的跟踪效果。
Secondly, we use the mean shift algorithm to track the faces. We realize automatic face tracking of image sequence eventually.
其次，在人脸跟踪方面采用基于均值平移的算法进行跟踪，最终实现图像序列的自动人脸跟踪。
Therefore, the kernel-tracking algorithm in our system is based on the mode of histogram and the search method of Mean Shift algorithm.
因此，本系统使用以直方图为模式特征，以均值平移算法为计算方法的实时跟踪算法为本系统的核心跟踪算法。
In the part of tracking, combining the improved Mean-Shift algorithm and Kalman filter prediction.
在跟踪部分，采用改进的均值漂移算法和卡尔曼滤波预测结合。
In the part of tracking, combining the improved Mean-Shift algorithm and Kalman filter prediction.
在跟踪部分，采用改进的均值漂移算法和卡尔曼滤波预测结合。
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