Mean shift, mode seeking, and clustering Export

@article{citeulike:2522867, abstract = {Mean shift, a simple interactive procedure that shifts each data point to the average of data points in its neighborhood is generalized and analyzed in the paper. This generalization makes some k-means like clustering algorithms its special cases. It is shown that mean shift is a mode-seeking process on the surface constructed with a \“shadow\” kernal. For Gaussian kernels, mean shift is a gradient mapping. Convergence is studied for mean shift iterations. Cluster analysis if treated as a deterministic problem of finding a fixed point of mean shift that characterizes the data. Applications in clustering and Hough transform are demonstrated. Mean shift is also considered as an evolutionary strategy that performs multistart global optimization}, author = {Cheng, Yizong}, booktitle = {Pattern Analysis and Machine Intelligence, IEEE Transactions on}, citeulike-article-id = {2522867}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/34.400568}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=400568}, day = {06}, doi = {10.1109/34.400568}, journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on}, keywords = {mean\_shift}, month = {August}, number = {8}, pages = {790--799}, posted-at = {2009-09-21 13:07:41}, priority = {2}, title = {Mean shift, mode seeking, and clustering}, url = {http://dx.doi.org/10.1109/34.400568}, volume = {17}, year = {2002} }

TY - JOUR ID - citeulike:2522867 L3 - citeulike-article-id:2522867 N2 - Mean shift, a simple interactive procedure that shifts each data point to the average of data points in its neighborhood is generalized and analyzed in the paper. This generalization makes some k-means like clustering algorithms its special cases. It is shown that mean shift is a mode-seeking process on the surface constructed with a “shadow” kernal. For Gaussian kernels, mean shift is a gradient mapping. Convergence is studied for mean shift iterations. Cluster analysis if treated as a deterministic problem of finding a fixed point of mean shift that characterizes the data. Applications in clustering and Hough transform are demonstrated. Mean shift is also considered as an evolutionary strategy that performs multistart global optimization IS - 8 JF - Pattern Analysis and Machine Intelligence, IEEE Transactions on EP - 799 TI - Mean shift, mode seeking, and clustering VL - 17 T2 - Pattern Analysis and Machine Intelligence, IEEE Transactions on SP - 790 KW - mean_shift AU - Cheng, Yizong PY - 2002/08/06/ UR - http://dx.doi.org/10.1109/34.400568 ER -