运动估计and tracking are key activities in many computer vision applications, including activity recognition, traffic monitoring, automotive safety, and surveillance.

计算机视觉工具箱™ provides video tracking algorithms, such as continuously adaptive mean shift (CAMShift) and Kanade-Lucas-Tomasi (KLT). You can use these algorithms for tracking a single object or as building blocks in a more complex tracking system. The toolbox also provides a framework for multiple object tracking that includes卡尔曼过滤以及用于为轨道分配对象检测的匈牙利算法。

运动估计is the process of determining the movement of blocks between adjacent video frames. This toolbox includes motion estimation algorithms, such as光流，块匹配和模板匹配。这些算法创建了运动向量，该运动向量可以与整个图像，块，任意补丁或单个像素有关。对于块和模板匹配，找到最佳匹配的评估指标包括均方根误差（MSE），平均绝对偏差（MAD），最大绝对差（最大），绝对差异（SAD）和平方差的总和（SSD）。