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在vs2010平台上运行的自适应均值漂移目标跟踪算法源程序，使用c++语言编写-Adaptive mean vs2010 platform running on shift target tracking algorithm source code, using language c++
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基于mean-shift算法的动目标跟踪，可以识别目标，并记录动目标的跟踪轨迹，并在窗口显示-Based on mean-shift algorithm of moving target tracking, you can identify the target, moving target tracking and recording tracks，and displayed in the window
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mean shift跟踪，椭圆大小及方向随物体运动而变化，始终能框住物体，论文和代码均在压缩包里面，亲测没有问题。-mean shift tracking, oval object the size and direction of the movement with the change, will always be able to frame objects, and code papers were compressed inside, pro-test is no problem.
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综合介绍meanshift算法的使用，使用meanshift算法对图像分割，在后续的运动跟踪埋下基础-This section describes the sum of the mean shift algorithm。Using mean shift algorithm for image segmentation, in a subsequent motion tracking laying foundation
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实现了运动目标的检测和跟踪，使用背景差分法，帧间差分法、光流法和均值漂移的方法，能够实现很好的对运动目标的跟踪-Achieve a moving target detection and tracking, using background subtraction, inter-frame difference, optical flow method and the method of mean-shift, it is possible to achieve a good track mov
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Mean shift tracking Algorithm
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meanshift均值平移跟踪算法中核函数窗宽的自动选取代码，根据目标大小变化核窗宽，使得当目标出现大小变化时准确跟踪到目标中心
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Meanshift mean shift tracking algorithm, kernel function window width automatic selection code, according to the target size changes in the width of the nuclear window, so that
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Meanshift均值漂移算法，图像中的物体进行跟踪定位。(Meanshift mean shift algorithm, tracking and positioning objects in the image.)
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通过手动框选目标区域，然后进行自动跟踪，使用的算法是Camshift，自适应均值漂移(By manually selecting the target area, then automatic tracking, using the algorithm is Camshift, adaptive mean shift)
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meanShift,均值漂移，在聚类、图像平滑、分割、跟踪等方面有着广泛的应用。一般是指一个迭代的步骤，即先算出当前点的偏移均值，然后以此为新的起始点，继续移动，直到满足一定的结束条件。(MeanShift, mean shift is widely used in clustering, image smoothing, segmentation, tracking and so on. Generally refers to an iterative step, that is, first
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1. 静态背景下的背景预测法目标检测
2. 静态背景下帧间差分法目标检测
3. Mean Shift目标跟踪方法
4. 重心多目标跟踪方法(1. Background prediction method background detection in static background
2. Inter-frame difference method target detection in static background
3. Mean Shift The target track
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