Introduction KErnel density Kernel choices I Peak finding I Mean-shift I Cam-shift kernel density distribution function K is a function To be explained(see slide 19) The general form of a kernel x-xi density distribution function x)=∑k The Kernel (k) has many n=number of samples choices h= window radius Epanechnikov d= dimension Uniform get position Normal ( gaussian) x= samples C= normalization constant Camshift v 0.aIntroduction | Kernel density | Kernel choices | Peak finding | Mean-shift | Cam-shift kernel density distribution function • The general form of a kernel density distribution function • The Kernel (K) has many choices – Epanechnikov – Uniform – Normal (Gaussian) C normalization constant samples target position dimension window radius number of samples ( ) ˆ 1 = = = = = =       − = = i n i i h d x xd h n h x x K nhC f x Camshift v.0.a 10 K is a function: To be explained (see slide19)