MeanShift算法详解以及matlab源码

[{"title":"（ 26 个子文件 11.44MB ） MeanShift算法详解以及matlab源码","children":[{"title":"MeanShift+深入详细(MatLab源码)","children":[{"title":"meanshift文章、PPT、word文档、基于meanshift的跟踪程序","children":[{"title":"An Introduction to Mean Shift.doc <span style='color:#111;'> 1.82MB </span>","children":null,"spread":false},{"title":"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","children":[{"title":"readme.m <span style='color:#111;'> 488B </span>","children":null,"spread":false},{"title":"show_target.m <span style='color:#111;'> 1.28KB </span>","children":null,"spread":false},{"title":"color_example.m <span style='color:#111;'> 2.83KB </span>","children":null,"spread":false},{"title":"compute_kernelmatrix.m <span style='color:#111;'> 1.18KB </span>","children":null,"spread":false},{"title":"track.m <span style='color:#111;'> 3.36KB </span>","children":null,"spread":false},{"title":"compute_k_hist.m <span style='color:#111;'> 4.17KB </span>","children":null,"spread":false},{"title":"color_object_tracking2.m <span style='color:#111;'> 2.81KB </span>","children":null,"spread":false},{"title":"compute_wi.m <span style='color:#111;'> 839B </span>","children":null,"spread":false},{"title":"object_tracking.m <span style='color:#111;'> 3.06KB </span>","children":null,"spread":false}],"spread":true},{"title":"mean_shift.ppt <span style='color:#111;'> 7.34MB </span>","children":null,"spread":false},{"title":"meanshift.pdf <span style='color:#111;'> 571.13KB </span>","children":null,"spread":false},{"title":"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","children":[{"title":"meanshift","children":[{"title":"getsimilarity.m <span style='color:#111;'> 931B </span>","children":null,"spread":false},{"title":"comparing.m <span style='color:#111;'> 512B </span>","children":null,"spread":false},{"title":"012.jpg <span style='color:#111;'> 99.25KB </span>","children":null,"spread":false},{"title":"013.jpg <span style='color:#111;'> 67.03KB </span>","children":null,"spread":false},{"title":"hs_err_pid4076.log <span style='color:#111;'> 7.43KB </span>","children":null,"spread":false},{"title":"myedge.m <span style='color:#111;'> 766B </span>","children":null,"spread":false},{"title":"meanshiftsmooth.m <span style='color:#111;'> 1.46KB </span>","children":null,"spread":false},{"title":"Thumbs.db <span style='color:#111;'> 6.00KB </span>","children":null,"spread":false},{"title":"get_cluster_property.m <span style='color:#111;'> 466B </span>","children":null,"spread":false},{"title":"getkernalmatrix.m <span style='color:#111;'> 243B </span>","children":null,"spread":false},{"title":"getmeanshiftsegment.m <span style='color:#111;'> 2.02KB </span>","children":null,"spread":false}],"spread":false}],"spread":true},{"title":"一个外国人写的很好的meanshift聚类算法，有例程，可运行","children":[{"title":"testMeanShift.m <span style='color:#111;'> 1001B </span>","children":null,"spread":false},{"title":"MeanShiftCluster.m <span style='color:#111;'> 6.15KB </span>","children":null,"spread":false},{"title":"Mean Shift A Robust Approach Toward Feature Space Analysis.pdf <span style='color:#111;'> 3.18MB </span>","children":null,"spread":false}],"spread":true}],"spread":true}],"spread":true}],"spread":true}]