[Insight-developers] Statistics: Mean shift mode estimator

[Jisung Kim]

Hi. I read the paper. The filtering and segmentation
methods seem to be a good example of kernel density
techniques. My k-d tree implementation probably
accelerate the mean shift vector calculation part
(range search). Even the non-terminal nodes of the k-d
tree store the vector sum and the number of
measurement vectors below each node. If nobody wants
to pursuit these methods, I want to try.


--- "Miller, James V (Research)" <millerjv at crd . ge . com>
wrote:
> Does anyone have plans to add a "mean shift" mode
> estimator to ITK?
>  
> http://www . computer . org/tpami/tp1995/i0790abs . htm
> <http://www . computer . org/tpami/tp1995/i0790abs . htm> 
>  
>
http://www . caip . rutgers . edu/~comanici/Papers/MsAnalysis . pdf
>
<http://www . caip . rutgers . edu/~comanici/Papers/MsAnalysis . pdf>
> 
>  
>  
>  
> 
> Jim Miller 
> _____________________________________
> Visualization & Computer Vision
> GE Research
> Bldg. KW, Room C218B
> P.O. Box 8, Schenectady NY 12301
> 
> millerjv at research . ge . com
> <mailto:millerjv at research . ge . com> 
> 
> james . miller at research . ge . com
> (518) 387-4005, Dial Comm: 8*833-4005, 
> Cell: (518) 505-7065, Fax: (518) 387-6981 
> 
>  
> 


=====
Jisung Kim
bahrahm at yahoo . com
106 Mason Farm Rd.
129 Radiology Research Lab., CB# 7515
Univ. of North Carolina at Chapel Hill
Chapel Hill, NC 27599-7515

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