--- /dev/null
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+// By downloading, copying, installing or using the software you agree to this license.
+// If you do not agree to this license, do not download, install,
+// copy or use the software.
+//
+//
+// Intel License Agreement
+// For Open Source Computer Vision Library
+//
+// Copyright (C) 2000, Intel Corporation, all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+// * Redistribution's of source code must retain the above copyright notice,
+// this list of conditions and the following disclaimer.
+//
+// * Redistribution's in binary form must reproduce the above copyright notice,
+// this list of conditions and the following disclaimer in the documentation
+// and/or other materials provided with the distribution.
+//
+// * The name of Intel Corporation may not be used to endorse or promote products
+// derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+/*
+ Partially based on Yossi Rubner code:
+ =========================================================================
+ emd.c
+
+ Last update: 3/14/98
+
+ An implementation of the Earth Movers Distance.
+ Based of the solution for the Transportation problem as described in
+ "Introduction to Mathematical Programming" by F. S. Hillier and
+ G. J. Lieberman, McGraw-Hill, 1990.
+
+ Copyright (C) 1998 Yossi Rubner
+ Computer Science Department, Stanford University
+ E-Mail: rubner@cs.stanford.edu URL: http://vision.stanford.edu/~rubner
+ ==========================================================================
+*/
+#include "_cv.h"
+
+#define MAX_ITERATIONS 500
+#define CV_EMD_INF ((float)1e20)
+#define CV_EMD_EPS ((float)1e-5)
+
+/* CvNode1D is used for lists, representing 1D sparse array */
+typedef struct CvNode1D
+{
+ float val;
+ struct CvNode1D *next;
+}
+CvNode1D;
+
+/* CvNode2D is used for lists, representing 2D sparse matrix */
+typedef struct CvNode2D
+{
+ float val;
+ struct CvNode2D *next[2]; /* next row & next column */
+ int i, j;
+}
+CvNode2D;
+
+
+typedef struct CvEMDState
+{
+ int ssize, dsize;
+
+ float **cost;
+ CvNode2D *_x;
+ CvNode2D *end_x;
+ CvNode2D *enter_x;
+ char **is_x;
+
+ CvNode2D **rows_x;
+ CvNode2D **cols_x;
+
+ CvNode1D *u;
+ CvNode1D *v;
+
+ int* idx1;
+ int* idx2;
+
+ /* find_loop buffers */
+ CvNode2D **loop;
+ char *is_used;
+
+ /* russel buffers */
+ float *s;
+ float *d;
+ float **delta;
+
+ float weight, max_cost;
+ char *buffer;
+}
+CvEMDState;
+
+/* static function declaration */
+static CvStatus icvInitEMD( const float *signature1, int size1,
+ const float *signature2, int size2,
+ int dims, CvDistanceFunction dist_func, void *user_param,
+ const float* cost, int cost_step,
+ CvEMDState * state, float *lower_bound,
+ char *local_buffer, int local_buffer_size );
+
+static CvStatus icvFindBasicVariables( float **cost, char **is_x,
+ CvNode1D * u, CvNode1D * v, int ssize, int dsize );
+
+static float icvIsOptimal( float **cost, char **is_x,
+ CvNode1D * u, CvNode1D * v,
+ int ssize, int dsize, CvNode2D * enter_x );
+
+static void icvRussel( CvEMDState * state );
+
+
+static CvStatus icvNewSolution( CvEMDState * state );
+static int icvFindLoop( CvEMDState * state );
+
+static void icvAddBasicVariable( CvEMDState * state,
+ int min_i, int min_j,
+ CvNode1D * prev_u_min_i,
+ CvNode1D * prev_v_min_j,
+ CvNode1D * u_head );
+
+static float icvDistL2( const float *x, const float *y, void *user_param );
+static float icvDistL1( const float *x, const float *y, void *user_param );
+static float icvDistC( const float *x, const float *y, void *user_param );
+
+/* The main function */
+CV_IMPL float
+cvCalcEMD2( const CvArr* signature_arr1,
+ const CvArr* signature_arr2,
+ int dist_type,
+ CvDistanceFunction dist_func,
+ const CvArr* cost_matrix,
+ CvArr* flow_matrix,
+ float *lower_bound,
+ void *user_param )
+{
+ char local_buffer[16384];
+ char *local_buffer_ptr = (char *)cvAlignPtr(local_buffer,16);
+ CvEMDState state;
+ float emd = 0;
+
+ CV_FUNCNAME( "cvCalcEMD2" );
+
+ memset( &state, 0, sizeof(state));
+
+ __BEGIN__;
+
+ double total_cost = 0;
+ CvStatus result = CV_NO_ERR;
+ float eps, min_delta;
+ CvNode2D *xp = 0;
+ CvMat sign_stub1, *signature1 = (CvMat*)signature_arr1;
+ CvMat sign_stub2, *signature2 = (CvMat*)signature_arr2;
+ CvMat cost_stub, *cost = &cost_stub;
+ CvMat flow_stub, *flow = (CvMat*)flow_matrix;
+ int dims, size1, size2;
+
+ CV_CALL( signature1 = cvGetMat( signature1, &sign_stub1 ));
+ CV_CALL( signature2 = cvGetMat( signature2, &sign_stub2 ));
+
+ if( signature1->cols != signature2->cols )
+ CV_ERROR( CV_StsUnmatchedSizes, "The arrays must have equal number of columns (which is number of dimensions but 1)" );
+
+ dims = signature1->cols - 1;
+ size1 = signature1->rows;
+ size2 = signature2->rows;
+
+ if( !CV_ARE_TYPES_EQ( signature1, signature2 ))
+ CV_ERROR( CV_StsUnmatchedFormats, "The array must have equal types" );
+
+ if( CV_MAT_TYPE( signature1->type ) != CV_32FC1 )
+ CV_ERROR( CV_StsUnsupportedFormat, "The signatures must be 32fC1" );
+
+ if( flow )
+ {
+ CV_CALL( flow = cvGetMat( flow, &flow_stub ));
+
+ if( flow->rows != size1 || flow->cols != size2 )
+ CV_ERROR( CV_StsUnmatchedSizes,
+ "The flow matrix size does not match to the signatures' sizes" );
+
+ if( CV_MAT_TYPE( flow->type ) != CV_32FC1 )
+ CV_ERROR( CV_StsUnsupportedFormat, "The flow matrix must be 32fC1" );
+ }
+
+ cost->data.fl = 0;
+ cost->step = 0;
+
+ if( dist_type < 0 )
+ {
+ if( cost_matrix )
+ {
+ if( dist_func )
+ CV_ERROR( CV_StsBadArg,
+ "Only one of cost matrix or distance function should be non-NULL in case of user-defined distance" );
+
+ if( lower_bound )
+ CV_ERROR( CV_StsBadArg,
+ "The lower boundary can not be calculated if the cost matrix is used" );
+
+ CV_CALL( cost = cvGetMat( cost_matrix, &cost_stub ));
+ if( cost->rows != size1 || cost->cols != size2 )
+ CV_ERROR( CV_StsUnmatchedSizes,
+ "The cost matrix size does not match to the signatures' sizes" );
+
+ if( CV_MAT_TYPE( cost->type ) != CV_32FC1 )
+ CV_ERROR( CV_StsUnsupportedFormat, "The cost matrix must be 32fC1" );
+ }
+ else if( !dist_func )
+ CV_ERROR( CV_StsNullPtr, "In case of user-defined distance Distance function is undefined" );
+ }
+ else
+ {
+ if( dims == 0 )
+ CV_ERROR( CV_StsBadSize,
+ "Number of dimensions can be 0 only if a user-defined metric is used" );
+ user_param = (void *) (size_t)dims;
+ switch (dist_type)
+ {
+ case CV_DIST_L1:
+ dist_func = icvDistL1;
+ break;
+ case CV_DIST_L2:
+ dist_func = icvDistL2;
+ break;
+ case CV_DIST_C:
+ dist_func = icvDistC;
+ break;
+ default:
+ CV_ERROR( CV_StsBadFlag, "Bad or unsupported metric type" );
+ }
+ }
+
+ IPPI_CALL( result = icvInitEMD( signature1->data.fl, size1,
+ signature2->data.fl, size2,
+ dims, dist_func, user_param,
+ cost->data.fl, cost->step,
+ &state, lower_bound, local_buffer_ptr,
+ sizeof( local_buffer ) - 16 ));
+
+ if( result > 0 && lower_bound )
+ {
+ emd = *lower_bound;
+ EXIT;
+ }
+
+ eps = CV_EMD_EPS * state.max_cost;
+
+ /* if ssize = 1 or dsize = 1 then we are done, else ... */
+ if( state.ssize > 1 && state.dsize > 1 )
+ {
+ int itr;
+
+ for( itr = 1; itr < MAX_ITERATIONS; itr++ )
+ {
+ /* find basic variables */
+ result = icvFindBasicVariables( state.cost, state.is_x,
+ state.u, state.v, state.ssize, state.dsize );
+ if( result < 0 )
+ break;
+
+ /* check for optimality */
+ min_delta = icvIsOptimal( state.cost, state.is_x,
+ state.u, state.v,
+ state.ssize, state.dsize, state.enter_x );
+
+ if( min_delta == CV_EMD_INF )
+ {
+ CV_ERROR( CV_StsNoConv, "" );
+ }
+
+ /* if no negative deltamin, we found the optimal solution */
+ if( min_delta >= -eps )
+ break;
+
+ /* improve solution */
+ IPPI_CALL( icvNewSolution( &state ));
+ }
+ }
+
+ /* compute the total flow */
+ for( xp = state._x; xp < state.end_x; xp++ )
+ {
+ float val = xp->val;
+ int i = xp->i;
+ int j = xp->j;
+ int ci = state.idx1[i];
+ int cj = state.idx2[j];
+
+ if( xp != state.enter_x && ci >= 0 && cj >= 0 )
+ {
+ total_cost += (double)val * state.cost[i][j];
+ if( flow )
+ ((float*)(flow->data.ptr + flow->step*ci))[cj] = val;
+ }
+ }
+
+ emd = (float) (total_cost / state.weight);
+
+ __END__;
+
+ if( state.buffer && state.buffer != local_buffer_ptr )
+ cvFree( &state.buffer );
+
+ return emd;
+}
+
+
+/************************************************************************************\
+* initialize structure, allocate buffers and generate initial golution *
+\************************************************************************************/
+static CvStatus
+icvInitEMD( const float* signature1, int size1,
+ const float* signature2, int size2,
+ int dims, CvDistanceFunction dist_func, void* user_param,
+ const float* cost, int cost_step,
+ CvEMDState* state, float* lower_bound,
+ char* local_buffer, int local_buffer_size )
+{
+ float s_sum = 0, d_sum = 0, diff;
+ int i, j;
+ int ssize = 0, dsize = 0;
+ int equal_sums = 1;
+ int buffer_size;
+ float max_cost = 0;
+ char *buffer, *buffer_end;
+
+ memset( state, 0, sizeof( *state ));
+ assert( cost_step % sizeof(float) == 0 );
+ cost_step /= sizeof(float);
+
+ /* calculate buffer size */
+ buffer_size = (size1+1) * (size2+1) * (sizeof( float ) + /* cost */
+ sizeof( char ) + /* is_x */
+ sizeof( float )) + /* delta matrix */
+ (size1 + size2 + 2) * (sizeof( CvNode2D ) + /* _x */
+ sizeof( CvNode2D * ) + /* cols_x & rows_x */
+ sizeof( CvNode1D ) + /* u & v */
+ sizeof( float ) + /* s & d */
+ sizeof( int ) + sizeof(CvNode2D*)) + /* idx1 & idx2 */
+ (size1+1) * (sizeof( float * ) + sizeof( char * ) + /* rows pointers for */
+ sizeof( float * )) + 256; /* cost, is_x and delta */
+
+ if( buffer_size < (int) (dims * 2 * sizeof( float )))
+ {
+ buffer_size = dims * 2 * sizeof( float );
+ }
+
+ /* allocate buffers */
+ if( local_buffer != 0 && local_buffer_size >= buffer_size )
+ {
+ buffer = local_buffer;
+ }
+ else
+ {
+ buffer = (char*)cvAlloc( buffer_size );
+ if( !buffer )
+ return CV_OUTOFMEM_ERR;
+ }
+
+ state->buffer = buffer;
+ buffer_end = buffer + buffer_size;
+
+ state->idx1 = (int*) buffer;
+ buffer += (size1 + 1) * sizeof( int );
+
+ state->idx2 = (int*) buffer;
+ buffer += (size2 + 1) * sizeof( int );
+
+ state->s = (float *) buffer;
+ buffer += (size1 + 1) * sizeof( float );
+
+ state->d = (float *) buffer;
+ buffer += (size2 + 1) * sizeof( float );
+
+ /* sum up the supply and demand */
+ for( i = 0; i < size1; i++ )
+ {
+ float weight = signature1[i * (dims + 1)];
+
+ if( weight > 0 )
+ {
+ s_sum += weight;
+ state->s[ssize] = weight;
+ state->idx1[ssize++] = i;
+
+ }
+ else if( weight < 0 )
+ return CV_BADRANGE_ERR;
+ }
+
+ for( i = 0; i < size2; i++ )
+ {
+ float weight = signature2[i * (dims + 1)];
+
+ if( weight > 0 )
+ {
+ d_sum += weight;
+ state->d[dsize] = weight;
+ state->idx2[dsize++] = i;
+ }
+ else if( weight < 0 )
+ return CV_BADRANGE_ERR;
+ }
+
+ if( ssize == 0 || dsize == 0 )
+ return CV_BADRANGE_ERR;
+
+ /* if supply different than the demand, add a zero-cost dummy cluster */
+ diff = s_sum - d_sum;
+ if( fabs( diff ) >= CV_EMD_EPS * s_sum )
+ {
+ equal_sums = 0;
+ if( diff < 0 )
+ {
+ state->s[ssize] = -diff;
+ state->idx1[ssize++] = -1;
+ }
+ else
+ {
+ state->d[dsize] = diff;
+ state->idx2[dsize++] = -1;
+ }
+ }
+
+ state->ssize = ssize;
+ state->dsize = dsize;
+ state->weight = s_sum > d_sum ? s_sum : d_sum;
+
+ if( lower_bound && equal_sums ) /* check lower bound */
+ {
+ int sz1 = size1 * (dims + 1), sz2 = size2 * (dims + 1);
+ float lb = 0;
+
+ float* xs = (float *) buffer;
+ float* xd = xs + dims;
+
+ memset( xs, 0, dims*sizeof(xs[0]));
+ memset( xd, 0, dims*sizeof(xd[0]));
+
+ for( j = 0; j < sz1; j += dims + 1 )
+ {
+ float weight = signature1[j];
+ for( i = 0; i < dims; i++ )
+ xs[i] += signature1[j + i + 1] * weight;
+ }
+
+ for( j = 0; j < sz2; j += dims + 1 )
+ {
+ float weight = signature2[j];
+ for( i = 0; i < dims; i++ )
+ xd[i] += signature2[j + i + 1] * weight;
+ }
+
+ lb = dist_func( xs, xd, user_param ) / state->weight;
+ i = *lower_bound <= lb;
+ *lower_bound = lb;
+ if( i )
+ return ( CvStatus ) 1;
+ }
+
+ /* assign pointers */
+ state->is_used = (char *) buffer;
+ /* init delta matrix */
+ state->delta = (float **) buffer;
+ buffer += ssize * sizeof( float * );
+
+ for( i = 0; i < ssize; i++ )
+ {
+ state->delta[i] = (float *) buffer;
+ buffer += dsize * sizeof( float );
+ }
+
+ state->loop = (CvNode2D **) buffer;
+ buffer += (ssize + dsize + 1) * sizeof(CvNode2D*);
+
+ state->_x = state->end_x = (CvNode2D *) buffer;
+ buffer += (ssize + dsize) * sizeof( CvNode2D );
+
+ /* init cost matrix */
+ state->cost = (float **) buffer;
+ buffer += ssize * sizeof( float * );
+
+ /* compute the distance matrix */
+ for( i = 0; i < ssize; i++ )
+ {
+ int ci = state->idx1[i];
+
+ state->cost[i] = (float *) buffer;
+ buffer += dsize * sizeof( float );
+
+ if( ci >= 0 )
+ {
+ for( j = 0; j < dsize; j++ )
+ {
+ int cj = state->idx2[j];
+ if( cj < 0 )
+ state->cost[i][j] = 0;
+ else
+ {
+ float val;
+ if( dist_func )
+ {
+ val = dist_func( signature1 + ci * (dims + 1) + 1,
+ signature2 + cj * (dims + 1) + 1,
+ user_param );
+ }
+ else
+ {
+ assert( cost );
+ val = cost[cost_step*ci + cj];
+ }
+ state->cost[i][j] = val;
+ if( max_cost < val )
+ max_cost = val;
+ }
+ }
+ }
+ else
+ {
+ for( j = 0; j < dsize; j++ )
+ state->cost[i][j] = 0;
+ }
+ }
+
+ state->max_cost = max_cost;
+
+ memset( buffer, 0, buffer_end - buffer );
+
+ state->rows_x = (CvNode2D **) buffer;
+ buffer += ssize * sizeof( CvNode2D * );
+
+ state->cols_x = (CvNode2D **) buffer;
+ buffer += dsize * sizeof( CvNode2D * );
+
+ state->u = (CvNode1D *) buffer;
+ buffer += ssize * sizeof( CvNode1D );
+
+ state->v = (CvNode1D *) buffer;
+ buffer += dsize * sizeof( CvNode1D );
+
+ /* init is_x matrix */
+ state->is_x = (char **) buffer;
+ buffer += ssize * sizeof( char * );
+
+ for( i = 0; i < ssize; i++ )
+ {
+ state->is_x[i] = buffer;
+ buffer += dsize;
+ }
+
+ assert( buffer <= buffer_end );
+
+ icvRussel( state );
+
+ state->enter_x = (state->end_x)++;
+ return CV_NO_ERR;
+}
+
+
+/****************************************************************************************\
+* icvFindBasicVariables *
+\****************************************************************************************/
+static CvStatus
+icvFindBasicVariables( float **cost, char **is_x,
+ CvNode1D * u, CvNode1D * v, int ssize, int dsize )
+{
+ int i, j, found;
+ int u_cfound, v_cfound;
+ CvNode1D u0_head, u1_head, *cur_u, *prev_u;
+ CvNode1D v0_head, v1_head, *cur_v, *prev_v;
+
+ /* initialize the rows list (u) and the columns list (v) */
+ u0_head.next = u;
+ for( i = 0; i < ssize; i++ )
+ {
+ u[i].next = u + i + 1;
+ }
+ u[ssize - 1].next = 0;
+ u1_head.next = 0;
+
+ v0_head.next = ssize > 1 ? v + 1 : 0;
+ for( i = 1; i < dsize; i++ )
+ {
+ v[i].next = v + i + 1;
+ }
+ v[dsize - 1].next = 0;
+ v1_head.next = 0;
+
+ /* there are ssize+dsize variables but only ssize+dsize-1 independent equations,
+ so set v[0]=0 */
+ v[0].val = 0;
+ v1_head.next = v;
+ v1_head.next->next = 0;
+
+ /* loop until all variables are found */
+ u_cfound = v_cfound = 0;
+ while( u_cfound < ssize || v_cfound < dsize )
+ {
+ found = 0;
+ if( v_cfound < dsize )
+ {
+ /* loop over all marked columns */
+ prev_v = &v1_head;
+
+ for( found |= (cur_v = v1_head.next) != 0; cur_v != 0; cur_v = cur_v->next )
+ {
+ float cur_v_val = cur_v->val;
+
+ j = (int)(cur_v - v);
+ /* find the variables in column j */
+ prev_u = &u0_head;
+ for( cur_u = u0_head.next; cur_u != 0; )
+ {
+ i = (int)(cur_u - u);
+ if( is_x[i][j] )
+ {
+ /* compute u[i] */
+ cur_u->val = cost[i][j] - cur_v_val;
+ /* ...and add it to the marked list */
+ prev_u->next = cur_u->next;
+ cur_u->next = u1_head.next;
+ u1_head.next = cur_u;
+ cur_u = prev_u->next;
+ }
+ else
+ {
+ prev_u = cur_u;
+ cur_u = cur_u->next;
+ }
+ }
+ prev_v->next = cur_v->next;
+ v_cfound++;
+ }
+ }
+
+ if( u_cfound < ssize )
+ {
+ /* loop over all marked rows */
+ prev_u = &u1_head;
+ for( found |= (cur_u = u1_head.next) != 0; cur_u != 0; cur_u = cur_u->next )
+ {
+ float cur_u_val = cur_u->val;
+ float *_cost;
+ char *_is_x;
+
+ i = (int)(cur_u - u);
+ _cost = cost[i];
+ _is_x = is_x[i];
+ /* find the variables in rows i */
+ prev_v = &v0_head;
+ for( cur_v = v0_head.next; cur_v != 0; )
+ {
+ j = (int)(cur_v - v);
+ if( _is_x[j] )
+ {
+ /* compute v[j] */
+ cur_v->val = _cost[j] - cur_u_val;
+ /* ...and add it to the marked list */
+ prev_v->next = cur_v->next;
+ cur_v->next = v1_head.next;
+ v1_head.next = cur_v;
+ cur_v = prev_v->next;
+ }
+ else
+ {
+ prev_v = cur_v;
+ cur_v = cur_v->next;
+ }
+ }
+ prev_u->next = cur_u->next;
+ u_cfound++;
+ }
+ }
+
+ if( !found )
+ {
+ return CV_NOTDEFINED_ERR;
+ }
+ }
+
+ return CV_NO_ERR;
+}
+
+
+/****************************************************************************************\
+* icvIsOptimal *
+\****************************************************************************************/
+static float
+icvIsOptimal( float **cost, char **is_x,
+ CvNode1D * u, CvNode1D * v, int ssize, int dsize, CvNode2D * enter_x )
+{
+ float delta, min_delta = CV_EMD_INF;
+ int i, j, min_i = 0, min_j = 0;
+
+ /* find the minimal cij-ui-vj over all i,j */
+ for( i = 0; i < ssize; i++ )
+ {
+ float u_val = u[i].val;
+ float *_cost = cost[i];
+ char *_is_x = is_x[i];
+
+ for( j = 0; j < dsize; j++ )
+ {
+ if( !_is_x[j] )
+ {
+ delta = _cost[j] - u_val - v[j].val;
+ if( min_delta > delta )
+ {
+ min_delta = delta;
+ min_i = i;
+ min_j = j;
+ }
+ }
+ }
+ }
+
+ enter_x->i = min_i;
+ enter_x->j = min_j;
+
+ return min_delta;
+}
+
+/****************************************************************************************\
+* icvNewSolution *
+\****************************************************************************************/
+static CvStatus
+icvNewSolution( CvEMDState * state )
+{
+ int i, j;
+ float min_val = CV_EMD_INF;
+ int steps;
+ CvNode2D head, *cur_x, *next_x, *leave_x = 0;
+ CvNode2D *enter_x = state->enter_x;
+ CvNode2D **loop = state->loop;
+
+ /* enter the new basic variable */
+ i = enter_x->i;
+ j = enter_x->j;
+ state->is_x[i][j] = 1;
+ enter_x->next[0] = state->rows_x[i];
+ enter_x->next[1] = state->cols_x[j];
+ enter_x->val = 0;
+ state->rows_x[i] = enter_x;
+ state->cols_x[j] = enter_x;
+
+ /* find a chain reaction */
+ steps = icvFindLoop( state );
+
+ if( steps == 0 )
+ return CV_NOTDEFINED_ERR;
+
+ /* find the largest value in the loop */
+ for( i = 1; i < steps; i += 2 )
+ {
+ float temp = loop[i]->val;
+
+ if( min_val > temp )
+ {
+ leave_x = loop[i];
+ min_val = temp;
+ }
+ }
+
+ /* update the loop */
+ for( i = 0; i < steps; i += 2 )
+ {
+ float temp0 = loop[i]->val + min_val;
+ float temp1 = loop[i + 1]->val - min_val;
+
+ loop[i]->val = temp0;
+ loop[i + 1]->val = temp1;
+ }
+
+ /* remove the leaving basic variable */
+ i = leave_x->i;
+ j = leave_x->j;
+ state->is_x[i][j] = 0;
+
+ head.next[0] = state->rows_x[i];
+ cur_x = &head;
+ while( (next_x = cur_x->next[0]) != leave_x )
+ {
+ cur_x = next_x;
+ assert( cur_x );
+ }
+ cur_x->next[0] = next_x->next[0];
+ state->rows_x[i] = head.next[0];
+
+ head.next[1] = state->cols_x[j];
+ cur_x = &head;
+ while( (next_x = cur_x->next[1]) != leave_x )
+ {
+ cur_x = next_x;
+ assert( cur_x );
+ }
+ cur_x->next[1] = next_x->next[1];
+ state->cols_x[j] = head.next[1];
+
+ /* set enter_x to be the new empty slot */
+ state->enter_x = leave_x;
+
+ return CV_NO_ERR;
+}
+
+
+
+/****************************************************************************************\
+* icvFindLoop *
+\****************************************************************************************/
+static int
+icvFindLoop( CvEMDState * state )
+{
+ int i, steps = 1;
+ CvNode2D *new_x;
+ CvNode2D **loop = state->loop;
+ CvNode2D *enter_x = state->enter_x, *_x = state->_x;
+ char *is_used = state->is_used;
+
+ memset( is_used, 0, state->ssize + state->dsize );
+
+ new_x = loop[0] = enter_x;
+ is_used[enter_x - _x] = 1;
+ steps = 1;
+
+ do
+ {
+ if( (steps & 1) == 1 )
+ {
+ /* find an unused x in the row */
+ new_x = state->rows_x[new_x->i];
+ while( new_x != 0 && is_used[new_x - _x] )
+ new_x = new_x->next[0];
+ }
+ else
+ {
+ /* find an unused x in the column, or the entering x */
+ new_x = state->cols_x[new_x->j];
+ while( new_x != 0 && is_used[new_x - _x] && new_x != enter_x )
+ new_x = new_x->next[1];
+ if( new_x == enter_x )
+ break;
+ }
+
+ if( new_x != 0 ) /* found the next x */
+ {
+ /* add x to the loop */
+ loop[steps++] = new_x;
+ is_used[new_x - _x] = 1;
+ }
+ else /* didn't find the next x */
+ {
+ /* backtrack */
+ do
+ {
+ i = steps & 1;
+ new_x = loop[steps - 1];
+ do
+ {
+ new_x = new_x->next[i];
+ }
+ while( new_x != 0 && is_used[new_x - _x] );
+
+ if( new_x == 0 )
+ {
+ is_used[loop[--steps] - _x] = 0;
+ }
+ }
+ while( new_x == 0 && steps > 0 );
+
+ is_used[loop[steps - 1] - _x] = 0;
+ loop[steps - 1] = new_x;
+ is_used[new_x - _x] = 1;
+ }
+ }
+ while( steps > 0 );
+
+ return steps;
+}
+
+
+
+/****************************************************************************************\
+* icvRussel *
+\****************************************************************************************/
+static void
+icvRussel( CvEMDState * state )
+{
+ int i, j, min_i = -1, min_j = -1;
+ float min_delta, diff;
+ CvNode1D u_head, *cur_u, *prev_u;
+ CvNode1D v_head, *cur_v, *prev_v;
+ CvNode1D *prev_u_min_i = 0, *prev_v_min_j = 0, *remember;
+ CvNode1D *u = state->u, *v = state->v;
+ int ssize = state->ssize, dsize = state->dsize;
+ float eps = CV_EMD_EPS * state->max_cost;
+ float **cost = state->cost;
+ float **delta = state->delta;
+
+ /* initialize the rows list (ur), and the columns list (vr) */
+ u_head.next = u;
+ for( i = 0; i < ssize; i++ )
+ {
+ u[i].next = u + i + 1;
+ }
+ u[ssize - 1].next = 0;
+
+ v_head.next = v;
+ for( i = 0; i < dsize; i++ )
+ {
+ v[i].val = -CV_EMD_INF;
+ v[i].next = v + i + 1;
+ }
+ v[dsize - 1].next = 0;
+
+ /* find the maximum row and column values (ur[i] and vr[j]) */
+ for( i = 0; i < ssize; i++ )
+ {
+ float u_val = -CV_EMD_INF;
+ float *cost_row = cost[i];
+
+ for( j = 0; j < dsize; j++ )
+ {
+ float temp = cost_row[j];
+
+ if( u_val < temp )
+ u_val = temp;
+ if( v[j].val < temp )
+ v[j].val = temp;
+ }
+ u[i].val = u_val;
+ }
+
+ /* compute the delta matrix */
+ for( i = 0; i < ssize; i++ )
+ {
+ float u_val = u[i].val;
+ float *delta_row = delta[i];
+ float *cost_row = cost[i];
+
+ for( j = 0; j < dsize; j++ )
+ {
+ delta_row[j] = cost_row[j] - u_val - v[j].val;
+ }
+ }
+
+ /* find the basic variables */
+ do
+ {
+ /* find the smallest delta[i][j] */
+ min_i = -1;
+ min_delta = CV_EMD_INF;
+ prev_u = &u_head;
+ for( cur_u = u_head.next; cur_u != 0; cur_u = cur_u->next )
+ {
+ i = (int)(cur_u - u);
+ float *delta_row = delta[i];
+
+ prev_v = &v_head;
+ for( cur_v = v_head.next; cur_v != 0; cur_v = cur_v->next )
+ {
+ j = (int)(cur_v - v);
+ if( min_delta > delta_row[j] )
+ {
+ min_delta = delta_row[j];
+ min_i = i;
+ min_j = j;
+ prev_u_min_i = prev_u;
+ prev_v_min_j = prev_v;
+ }
+ prev_v = cur_v;
+ }
+ prev_u = cur_u;
+ }
+
+ if( min_i < 0 )
+ break;
+
+ /* add x[min_i][min_j] to the basis, and adjust supplies and cost */
+ remember = prev_u_min_i->next;
+ icvAddBasicVariable( state, min_i, min_j, prev_u_min_i, prev_v_min_j, &u_head );
+
+ /* update the necessary delta[][] */
+ if( remember == prev_u_min_i->next ) /* line min_i was deleted */
+ {
+ for( cur_v = v_head.next; cur_v != 0; cur_v = cur_v->next )
+ {
+ j = (int)(cur_v - v);
+ if( cur_v->val == cost[min_i][j] ) /* column j needs updating */
+ {
+ float max_val = -CV_EMD_INF;
+
+ /* find the new maximum value in the column */
+ for( cur_u = u_head.next; cur_u != 0; cur_u = cur_u->next )
+ {
+ float temp = cost[cur_u - u][j];
+
+ if( max_val < temp )
+ max_val = temp;
+ }
+
+ /* if needed, adjust the relevant delta[*][j] */
+ diff = max_val - cur_v->val;
+ cur_v->val = max_val;
+ if( fabs( diff ) < eps )
+ {
+ for( cur_u = u_head.next; cur_u != 0; cur_u = cur_u->next )
+ delta[cur_u - u][j] += diff;
+ }
+ }
+ }
+ }
+ else /* column min_j was deleted */
+ {
+ for( cur_u = u_head.next; cur_u != 0; cur_u = cur_u->next )
+ {
+ i = (int)(cur_u - u);
+ if( cur_u->val == cost[i][min_j] ) /* row i needs updating */
+ {
+ float max_val = -CV_EMD_INF;
+
+ /* find the new maximum value in the row */
+ for( cur_v = v_head.next; cur_v != 0; cur_v = cur_v->next )
+ {
+ float temp = cost[i][cur_v - v];
+
+ if( max_val < temp )
+ max_val = temp;
+ }
+
+ /* if needed, adjust the relevant delta[i][*] */
+ diff = max_val - cur_u->val;
+ cur_u->val = max_val;
+
+ if( fabs( diff ) < eps )
+ {
+ for( cur_v = v_head.next; cur_v != 0; cur_v = cur_v->next )
+ delta[i][cur_v - v] += diff;
+ }
+ }
+ }
+ }
+ }
+ while( u_head.next != 0 || v_head.next != 0 );
+}
+
+
+
+/****************************************************************************************\
+* icvAddBasicVariable *
+\****************************************************************************************/
+static void
+icvAddBasicVariable( CvEMDState * state,
+ int min_i, int min_j,
+ CvNode1D * prev_u_min_i, CvNode1D * prev_v_min_j, CvNode1D * u_head )
+{
+ float temp;
+ CvNode2D *end_x = state->end_x;
+
+ if( state->s[min_i] < state->d[min_j] + state->weight * CV_EMD_EPS )
+ { /* supply exhausted */
+ temp = state->s[min_i];
+ state->s[min_i] = 0;
+ state->d[min_j] -= temp;
+ }
+ else /* demand exhausted */
+ {
+ temp = state->d[min_j];
+ state->d[min_j] = 0;
+ state->s[min_i] -= temp;
+ }
+
+ /* x(min_i,min_j) is a basic variable */
+ state->is_x[min_i][min_j] = 1;
+
+ end_x->val = temp;
+ end_x->i = min_i;
+ end_x->j = min_j;
+ end_x->next[0] = state->rows_x[min_i];
+ end_x->next[1] = state->cols_x[min_j];
+ state->rows_x[min_i] = end_x;
+ state->cols_x[min_j] = end_x;
+ state->end_x = end_x + 1;
+
+ /* delete supply row only if the empty, and if not last row */
+ if( state->s[min_i] == 0 && u_head->next->next != 0 )
+ prev_u_min_i->next = prev_u_min_i->next->next; /* remove row from list */
+ else
+ prev_v_min_j->next = prev_v_min_j->next->next; /* remove column from list */
+}
+
+
+/****************************************************************************************\
+* standard metrics *
+\****************************************************************************************/
+static float
+icvDistL1( const float *x, const float *y, void *user_param )
+{
+ int i, dims = (int)(size_t)user_param;
+ double s = 0;
+
+ for( i = 0; i < dims; i++ )
+ {
+ double t = x[i] - y[i];
+
+ s += fabs( t );
+ }
+ return (float)s;
+}
+
+static float
+icvDistL2( const float *x, const float *y, void *user_param )
+{
+ int i, dims = (int)(size_t)user_param;
+ double s = 0;
+
+ for( i = 0; i < dims; i++ )
+ {
+ double t = x[i] - y[i];
+
+ s += t * t;
+ }
+ return cvSqrt( (float)s );
+}
+
+static float
+icvDistC( const float *x, const float *y, void *user_param )
+{
+ int i, dims = (int)(size_t)user_param;
+ double s = 0;
+
+ for( i = 0; i < dims; i++ )
+ {
+ double t = fabs( x[i] - y[i] );
+
+ if( s < t )
+ s = t;
+ }
+ return (float)s;
+}
+
+/* End of file. */
+
projects / opencv / blobdiff