kernels.cpp
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00034 
00035 #include <cpl_visual_features/features/kernels.h>
00036 #include <math.h>
00037 
00038 namespace cpl_visual_features
00039 {
00040 
00041 double chiSqaureKernel(std::vector<double> x, std::vector<double> y)
00042 {
00043   double kernel_sum = 0.0;
00044   for (unsigned int i = 0; i < x.size(); ++i)
00045   {
00046     double numerator = x[i]-y[i];
00047     double a_plus_b = x[i]+y[i];
00048     if (a_plus_b > 0.0)
00049     {
00050       kernel_sum += (numerator*numerator)/a_plus_b;
00051     }
00052   }
00053   return kernel_sum;
00054 }
00055 
00056 std::vector<std::vector<double> > chiSquareKernelBatch(std::vector<std::vector<double> >& X,
00057                                                        std::vector<std::vector<double> >& Y, double gamma)
00058 {
00059   std::vector<std::vector<double> > K;
00060 
00061   // Compute chi-square elementwise
00062   for (int i = 0; i < X.size(); ++i)
00063   {
00064     std::vector<double> x = X[i];
00065     std::vector<double> row;
00066     K.push_back(row);
00067     for (int j = 0; j < Y.size(); ++j)
00068     {
00069       std::vector<double> y = Y[j];
00070       K[i].push_back(cpl_visual_features::chiSqaureKernel(x, y));
00071     }
00072   }
00073   if (gamma > 0.0)
00074   {
00075     for (int i = 0; i < K.size(); ++i)
00076     {
00077       for (int j = 0; j < K[i].size(); ++j)
00078       {
00079         K[i][j] = exp(-gamma*K[i][j]);
00080       }
00081     }
00082   }
00083   return K;
00084 }
00085 
00086 };


cpl_visual_features
Author(s): Tucker Hermans
autogenerated on Wed Nov 27 2013 11:52:36