The performance of visual target tracking algorithm using color histograms as tracking cues is always affected by illumination, visual angle and camera parameters.

MeanShift+深入详细(MatLab源码)\meanshift文章、PPT、word文档、基于meanshift的跟踪程序\An Introduction to Mean Shift.doc
..............................\.....................................................\meanshift.pdf
..............................\.....................................................\.........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\color_example.m
..............................\.....................................................\.......................................................................................................................\color_object_tracking2.m
..............................\.....................................................\.......................................................................................................................\compute_kernelmatrix.m
..............................\.....................................................\.......................................................................................................................\compute_k_hist.m
..............................\.....................................................\.......................................................................................................................\compute_wi.m
..............................\.....................................................\.......................................................................................................................\object_tracking.m
..............................\.....................................................\.......................................................................................................................\readme.m
..............................\.....................................................\.......................................................................................................................\show_target.m
..............................\.....................................................\.......................................................................................................................\track.m
..............................\.....................................................\mean_shift.ppt
..............................\.....................................................\一个外国人写的很好的meanshift聚类算法，有例程，可运行\Mean Shift A Robust Approach Toward Feature Space Analysis.pdf
..............................\.....................................................\.....................................................\MeanShiftCluster.m
..............................\.....................................................\.....................................................\testMeanShift.m
..............................\.....................................................\实现了基于mean-shift的图像检索，实现了比较两图像的相似度，选择最相近的图片\meanshift\012.jpg
..............................\.....................................................\..........................................................................\.........\013.jpg
..............................\.....................................................\..........................................................................\.........\comparing.m
..............................\.....................................................\..........................................................................\.........\getkernalmatrix.m
..............................\.....................................................\..........................................................................\.........\getmeanshiftsegment.m
..............................\.....................................................\..........................................................................\.........\getsimilarity.m
..............................\.....................................................\..........................................................................\.......

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