Added two kernels to existing SVM framework
Histogram intersection kernel (accessible by using SVM::INTER in CV namespace as kernel_type) Exponetial chi2 kernel (accessible by using SVM::CHI2 in CV namespace as kernel_type) Formulars: Exp-CHI2 k(x,y) = exp(-gamma * CHI2(x,y)) CHI2(x,y) = 1- 2* SUM_i[(xi-yi)²/(xi+yi)] Intersec k(x,y) = SUM_i[min(xi,yi)]
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@@ -297,7 +297,7 @@ struct CV_EXPORTS_W_MAP CvSVMParams
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CV_PROP_RW int svm_type;
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CV_PROP_RW int svm_type;
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CV_PROP_RW int kernel_type;
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CV_PROP_RW int kernel_type;
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CV_PROP_RW double degree; // for poly
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CV_PROP_RW double degree; // for poly
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CV_PROP_RW double gamma; // for poly/rbf/sigmoid
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CV_PROP_RW double gamma; // for poly/rbf/sigmoid/chi2
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CV_PROP_RW double coef0; // for poly/sigmoid
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CV_PROP_RW double coef0; // for poly/sigmoid
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CV_PROP_RW double C; // for CV_SVM_C_SVC, CV_SVM_EPS_SVR and CV_SVM_NU_SVR
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CV_PROP_RW double C; // for CV_SVM_C_SVC, CV_SVM_EPS_SVR and CV_SVM_NU_SVR
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@@ -326,7 +326,10 @@ struct CV_EXPORTS CvSVMKernel
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virtual void calc_non_rbf_base( int vec_count, int vec_size, const float** vecs,
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virtual void calc_non_rbf_base( int vec_count, int vec_size, const float** vecs,
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const float* another, float* results,
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const float* another, float* results,
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double alpha, double beta );
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double alpha, double beta );
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virtual void calc_intersec( int vcount, int var_count, const float** vecs,
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const float* another, float* results );
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virtual void calc_chi2( int vec_count, int vec_size, const float** vecs,
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const float* another, float* results );
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virtual void calc_linear( int vec_count, int vec_size, const float** vecs,
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virtual void calc_linear( int vec_count, int vec_size, const float** vecs,
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const float* another, float* results );
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const float* another, float* results );
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virtual void calc_rbf( int vec_count, int vec_size, const float** vecs,
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virtual void calc_rbf( int vec_count, int vec_size, const float** vecs,
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@@ -456,7 +459,7 @@ public:
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enum { C_SVC=100, NU_SVC=101, ONE_CLASS=102, EPS_SVR=103, NU_SVR=104 };
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enum { C_SVC=100, NU_SVC=101, ONE_CLASS=102, EPS_SVR=103, NU_SVR=104 };
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// SVM kernel type
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// SVM kernel type
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enum { LINEAR=0, POLY=1, RBF=2, SIGMOID=3 };
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enum { LINEAR=0, POLY=1, RBF=2, SIGMOID=3, CHI2=4, INTER=5 };
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// SVM params type
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// SVM params type
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enum { C=0, GAMMA=1, P=2, NU=3, COEF=4, DEGREE=5 };
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enum { C=0, GAMMA=1, P=2, NU=3, COEF=4, DEGREE=5 };
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@@ -220,6 +220,8 @@ bool CvSVMKernel::create( const CvSVMParams* _params, Calc _calc_func )
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calc_func = params->kernel_type == CvSVM::RBF ? &CvSVMKernel::calc_rbf :
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calc_func = params->kernel_type == CvSVM::RBF ? &CvSVMKernel::calc_rbf :
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params->kernel_type == CvSVM::POLY ? &CvSVMKernel::calc_poly :
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params->kernel_type == CvSVM::POLY ? &CvSVMKernel::calc_poly :
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params->kernel_type == CvSVM::SIGMOID ? &CvSVMKernel::calc_sigmoid :
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params->kernel_type == CvSVM::SIGMOID ? &CvSVMKernel::calc_sigmoid :
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params->kernel_type == CvSVM::CHI2 ? &CvSVMKernel::calc_chi2 :
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params->kernel_type == CvSVM::INTER ? &CvSVMKernel::calc_intersec :
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&CvSVMKernel::calc_linear;
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&CvSVMKernel::calc_linear;
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return true;
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return true;
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@@ -318,6 +320,52 @@ void CvSVMKernel::calc_rbf( int vcount, int var_count, const float** vecs,
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cvExp( &R, &R );
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cvExp( &R, &R );
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}
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}
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/// Histogram intersection kernel
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void CvSVMKernel::calc_intersec( int vcount, int var_count, const float** vecs,
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const float* another, Qfloat* results )
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{
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int j, k;
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for( j = 0; j < vcount; j++ )
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{
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const float* sample = vecs[j];
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double s = 0;
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for( k = 0; k <= var_count - 4; k += 4 )
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s += min(sample[k],another[k]) + min(sample[k+1],another[k+1]) +
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min(sample[k+2],another[k+2]) + min(sample[k+3],another[k+3]);
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for( ; k < var_count; k++ )
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s += min(sample[k],another[k]);
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results[j] = (Qfloat)(s);
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}
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}
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/// Exponential chi2 kernel
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void CvSVMKernel::calc_chi2( int vcount, int var_count, const float** vecs,
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const float* another, Qfloat* results )
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{
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CvMat R = cvMat( 1, vcount, QFLOAT_TYPE, results );
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double gamma = -params->gamma;
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int j, k;
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for( j = 0; j < vcount; j++ )
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{
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const float* sample = vecs[j];
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double chi2 = 0;
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for(k = 0 ; k < var_count; k++ )
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{
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double d = sample[k]*another[k];
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double devisor = sample[k]+another[k];
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/// if devisor == 0, the Chi2 distance would be zero, but calculation would rise an error because of deviding by zero
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if (devisor != 0)
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{
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chi2 += d*d/devisor;
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}
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}
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results[j] = (Qfloat) (gamma*(1.0-2*chi2));
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}
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if( vcount > 0 )
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cvExp( &R, &R );
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}
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void CvSVMKernel::calc( int vcount, int var_count, const float** vecs,
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void CvSVMKernel::calc( int vcount, int var_count, const float** vecs,
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const float* another, Qfloat* results )
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const float* another, Qfloat* results )
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