cvaux.h - Android社区 - https://www.androidos.net.cn/

/*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*/

#ifndef __CVAUX__H__
#define __CVAUX__H__

#include "cv.h"

#ifdef __cplusplus
extern "C" {
#endif

CVAPI(CvSeq*) cvSegmentImage( const CvArr* srcarr, CvArr* dstarr,
                                    double canny_threshold,
                                    double ffill_threshold,
                                    CvMemStorage* storage );

/****************************************************************************************\
*                                  Eigen objects                                         *
\****************************************************************************************/

typedef int (CV_CDECL * CvCallback)(int index, void* buffer, void* user_data);
typedef union
{
    CvCallback callback;
    void* data;
}
CvInput;

#define CV_EIGOBJ_NO_CALLBACK     0
#define CV_EIGOBJ_INPUT_CALLBACK  1
#define CV_EIGOBJ_OUTPUT_CALLBACK 2
#define CV_EIGOBJ_BOTH_CALLBACK   3

/* Calculates covariation matrix of a set of arrays */
CVAPI(void)  cvCalcCovarMatrixEx( int nObjects, void* input, int ioFlags,
                                  int ioBufSize, uchar* buffer, void* userData,
                                  IplImage* avg, float* covarMatrix );

/* Calculates eigen values and vectors of covariation matrix of a set of
   arrays */
CVAPI(void)  cvCalcEigenObjects( int nObjects, void* input, void* output,
                                 int ioFlags, int ioBufSize, void* userData,
                                 CvTermCriteria* calcLimit, IplImage* avg,
                                 float* eigVals );

/* Calculates dot product (obj - avg) * eigObj (i.e. projects image to eigen vector) */
CVAPI(double)  cvCalcDecompCoeff( IplImage* obj, IplImage* eigObj, IplImage* avg );

/* Projects image to eigen space (finds all decomposion coefficients */
CVAPI(void)  cvEigenDecomposite( IplImage* obj, int nEigObjs, void* eigInput,
                                 int ioFlags, void* userData, IplImage* avg,
                                 float* coeffs );

/* Projects original objects used to calculate eigen space basis to that space */
CVAPI(void)  cvEigenProjection( void* eigInput, int nEigObjs, int ioFlags,
                                void* userData, float* coeffs, IplImage* avg,
                                IplImage* proj );

/****************************************************************************************\
*                                       1D/2D HMM                                        *
\****************************************************************************************/

typedef struct CvImgObsInfo
{
    int obs_x;
    int obs_y;
    int obs_size;
    float* obs;//consequtive observations

int* state;/* arr of pairs superstate/state to which observation belong */
    int* mix;  /* number of mixture to which observation belong */

}
CvImgObsInfo;/*struct for 1 image*/

typedef CvImgObsInfo Cv1DObsInfo;

typedef struct CvEHMMState
{
    int num_mix;        /*number of mixtures in this state*/
    float* mu;          /*mean vectors corresponding to each mixture*/
    float* inv_var;     /* square root of inversed variances corresp. to each mixture*/
    float* log_var_val; /* sum of 0.5 (LN2PI + ln(variance[i]) ) for i=1,n */
    float* weight;      /*array of mixture weights. Summ of all weights in state is 1. */

}
CvEHMMState;

typedef struct CvEHMM
{
    int level; /* 0 - lowest(i.e its states are real states), ..... */
    int num_states; /* number of HMM states */
    float*  transP;/*transition probab. matrices for states */
    float** obsProb; /* if level == 0 - array of brob matrices corresponding to hmm
                        if level == 1 - martix of matrices */
    union
    {
        CvEHMMState* state; /* if level == 0 points to real states array,
                               if not - points to embedded hmms */
        struct CvEHMM* ehmm; /* pointer to an embedded model or NULL, if it is a leaf */
    } u;

}
CvEHMM;

/*CVAPI(int)  icvCreate1DHMM( CvEHMM** this_hmm,
                                   int state_number, int* num_mix, int obs_size );

CVAPI(int)  icvRelease1DHMM( CvEHMM** phmm );

CVAPI(int)  icvUniform1DSegm( Cv1DObsInfo* obs_info, CvEHMM* hmm );

CVAPI(int)  icvInit1DMixSegm( Cv1DObsInfo** obs_info_array, int num_img, CvEHMM* hmm);

CVAPI(int)  icvEstimate1DHMMStateParams( CvImgObsInfo** obs_info_array, int num_img, CvEHMM* hmm);

CVAPI(int)  icvEstimate1DObsProb( CvImgObsInfo* obs_info, CvEHMM* hmm );

CVAPI(int)  icvEstimate1DTransProb( Cv1DObsInfo** obs_info_array,
                                           int num_seq,
                                           CvEHMM* hmm );

CVAPI(float)  icvViterbi( Cv1DObsInfo* obs_info, CvEHMM* hmm);

CVAPI(int)  icv1DMixSegmL2( CvImgObsInfo** obs_info_array, int num_img, CvEHMM* hmm );*/

/*********************************** Embedded HMMs *************************************/

/* Creates 2D HMM */
CVAPI(CvEHMM*)  cvCreate2DHMM( int* stateNumber, int* numMix, int obsSize );

/* Releases HMM */
CVAPI(void)  cvRelease2DHMM( CvEHMM** hmm );

#define CV_COUNT_OBS(roi, win, delta, numObs )                                       \
{                                                                                    \
   (numObs)->width  =((roi)->width  -(win)->width  +(delta)->width)/(delta)->width;  \
   (numObs)->height =((roi)->height -(win)->height +(delta)->height)/(delta)->height;\
}

/* Creates storage for observation vectors */
CVAPI(CvImgObsInfo*)  cvCreateObsInfo( CvSize numObs, int obsSize );

/* Releases storage for observation vectors */
CVAPI(void)  cvReleaseObsInfo( CvImgObsInfo** obs_info );

/* The function takes an image on input and and returns the sequnce of observations
   to be used with an embedded HMM; Each observation is top-left block of DCT
   coefficient matrix */
CVAPI(void)  cvImgToObs_DCT( const CvArr* arr, float* obs, CvSize dctSize,
                             CvSize obsSize, CvSize delta );

/* Uniformly segments all observation vectors extracted from image */
CVAPI(void)  cvUniformImgSegm( CvImgObsInfo* obs_info, CvEHMM* ehmm );

/* Does mixture segmentation of the states of embedded HMM */
CVAPI(void)  cvInitMixSegm( CvImgObsInfo** obs_info_array,
                            int num_img, CvEHMM* hmm );

/* Function calculates means, variances, weights of every Gaussian mixture
   of every low-level state of embedded HMM */
CVAPI(void)  cvEstimateHMMStateParams( CvImgObsInfo** obs_info_array,
                                       int num_img, CvEHMM* hmm );

/* Function computes transition probability matrices of embedded HMM
   given observations segmentation */
CVAPI(void)  cvEstimateTransProb( CvImgObsInfo** obs_info_array,
                                  int num_img, CvEHMM* hmm );

/* Function computes probabilities of appearing observations at any state
   (i.e. computes P(obs|state) for every pair(obs,state)) */
CVAPI(void)  cvEstimateObsProb( CvImgObsInfo* obs_info,
                                CvEHMM* hmm );

/* Runs Viterbi algorithm for embedded HMM */
CVAPI(float)  cvEViterbi( CvImgObsInfo* obs_info, CvEHMM* hmm );

/* Function clusters observation vectors from several images
   given observations segmentation.
   Euclidean distance used for clustering vectors.
   Centers of clusters are given means of every mixture */
CVAPI(void)  cvMixSegmL2( CvImgObsInfo** obs_info_array,
                          int num_img, CvEHMM* hmm );

/****************************************************************************************\
*               A few functions from old stereo gesture recognition demosions            *
\****************************************************************************************/

/* Creates hand mask image given several points on the hand */
CVAPI(void)  cvCreateHandMask( CvSeq* hand_points,
                                   IplImage *img_mask, CvRect *roi);

/* Finds hand region in range image data */
CVAPI(void)  cvFindHandRegion (CvPoint3D32f* points, int count,
                                CvSeq* indexs,
                                float* line, CvSize2D32f size, int flag,
                                CvPoint3D32f* center,
                                CvMemStorage* storage, CvSeq **numbers);

/* Finds hand region in range image data (advanced version) */
CVAPI(void)  cvFindHandRegionA( CvPoint3D32f* points, int count,
                                CvSeq* indexs,
                                float* line, CvSize2D32f size, int jc,
                                CvPoint3D32f* center,
                                CvMemStorage* storage, CvSeq **numbers);

/****************************************************************************************\
*                           Additional operations on Subdivisions                        *
\****************************************************************************************/

// paints voronoi diagram: just demo function
CVAPI(void)  icvDrawMosaic( CvSubdiv2D* subdiv, IplImage* src, IplImage* dst );

// checks planar subdivision for correctness. It is not an absolute check,
// but it verifies some relations between quad-edges
CVAPI(int)   icvSubdiv2DCheck( CvSubdiv2D* subdiv );

// returns squared distance between two 2D points with floating-point coordinates.
CV_INLINE double icvSqDist2D32f( CvPoint2D32f pt1, CvPoint2D32f pt2 )
{
    double dx = pt1.x - pt2.x;
    double dy = pt1.y - pt2.y;

return dx*dx + dy*dy;
}

/****************************************************************************************\
*                           More operations on sequences                                 *
\****************************************************************************************/

/*****************************************************************************************/

#define CV_CURRENT_INT( reader ) (*((int *)(reader).ptr))
#define CV_PREV_INT( reader ) (*((int *)(reader).prev_elem))

#define  CV_GRAPH_WEIGHTED_VERTEX_FIELDS() CV_GRAPH_VERTEX_FIELDS()\
    float weight;

#define  CV_GRAPH_WEIGHTED_EDGE_FIELDS() CV_GRAPH_EDGE_FIELDS()

typedef struct CvGraphWeightedVtx
{
    CV_GRAPH_WEIGHTED_VERTEX_FIELDS()
}
CvGraphWeightedVtx;

typedef struct CvGraphWeightedEdge
{
    CV_GRAPH_WEIGHTED_EDGE_FIELDS()
}
CvGraphWeightedEdge;

typedef enum CvGraphWeightType
{
    CV_NOT_WEIGHTED,
    CV_WEIGHTED_VTX,
    CV_WEIGHTED_EDGE,
    CV_WEIGHTED_ALL
} CvGraphWeightType;

/*****************************************************************************************/

/*******************************Stereo correspondence*************************************/

typedef struct CvCliqueFinder
{   
    CvGraph* graph;
    int**    adj_matr;
    int N; //graph size

// stacks, counters etc/
    int k; //stack size
    int* current_comp;
    int** All;
    
    int* ne;
    int* ce;
    int* fixp; //node with minimal disconnections
    int* nod;
    int* s; //for selected candidate
    int status;
    int best_score;
    int weighted;
    int weighted_edges;    
    float best_weight;
    float* edge_weights;
    float* vertex_weights;
    float* cur_weight;
    float* cand_weight;

} CvCliqueFinder;

#define CLIQUE_TIME_OFF 2
#define CLIQUE_FOUND 1
#define CLIQUE_END   0

/*CVAPI(void) cvStartFindCliques( CvGraph* graph, CvCliqueFinder* finder, int reverse, 
                                   int weighted CV_DEFAULT(0),  int weighted_edges CV_DEFAULT(0));
CVAPI(int) cvFindNextMaximalClique( CvCliqueFinder* finder, int* clock_rest CV_DEFAULT(0) ); 
CVAPI(void) cvEndFindCliques( CvCliqueFinder* finder );

CVAPI(void) cvBronKerbosch( CvGraph* graph );*/

/*F///////////////////////////////////////////////////////////////////////////////////////
//
//    Name:    cvSubgraphWeight
//    Purpose: finds weight of subgraph in a graph
//    Context:
//    Parameters:
//      graph - input graph.
//      subgraph - sequence of pairwise different ints.  These are indices of vertices of subgraph.
//      weight_type - describes the way we measure weight.
//            one of the following:
//            CV_NOT_WEIGHTED - weight of a clique is simply its size
//            CV_WEIGHTED_VTX - weight of a clique is the sum of weights of its vertices
//            CV_WEIGHTED_EDGE - the same but edges
//            CV_WEIGHTED_ALL - the same but both edges and vertices
//      weight_vtx - optional vector of floats, with size = graph->total.
//            If weight_type is either CV_WEIGHTED_VTX or CV_WEIGHTED_ALL
//            weights of vertices must be provided.  If weight_vtx not zero
//            these weights considered to be here, otherwise function assumes
//            that vertices of graph are inherited from CvGraphWeightedVtx.
//      weight_edge - optional matrix of floats, of width and height = graph->total.
//            If weight_type is either CV_WEIGHTED_EDGE or CV_WEIGHTED_ALL
//            weights of edges ought to be supplied.  If weight_edge is not zero
//            function finds them here, otherwise function expects
//            edges of graph to be inherited from CvGraphWeightedEdge.
//            If this parameter is not zero structure of the graph is determined from matrix
//            rather than from CvGraphEdge's.  In particular, elements corresponding to
//            absent edges should be zero.
//    Returns:
//      weight of subgraph.
//    Notes:
//F*/
/*CVAPI(float) cvSubgraphWeight( CvGraph *graph, CvSeq *subgraph,
                                  CvGraphWeightType weight_type CV_DEFAULT(CV_NOT_WEIGHTED),
                                  CvVect32f weight_vtx CV_DEFAULT(0),
                                  CvMatr32f weight_edge CV_DEFAULT(0) );*/

/*F///////////////////////////////////////////////////////////////////////////////////////
//
//    Name:    cvFindCliqueEx
//    Purpose: tries to find clique with maximum possible weight in a graph
//    Context:
//    Parameters:
//      graph - input graph.
//      storage - memory storage to be used by the result.
//      is_complementary - optional flag showing whether function should seek for clique
//            in complementary graph.
//      weight_type - describes our notion about weight.
//            one of the following:
//            CV_NOT_WEIGHTED - weight of a clique is simply its size
//            CV_WEIGHTED_VTX - weight of a clique is the sum of weights of its vertices
//            CV_WEIGHTED_EDGE - the same but edges
//            CV_WEIGHTED_ALL - the same but both edges and vertices
//      weight_vtx - optional vector of floats, with size = graph->total.
//            If weight_type is either CV_WEIGHTED_VTX or CV_WEIGHTED_ALL
//            weights of vertices must be provided.  If weight_vtx not zero
//            these weights considered to be here, otherwise function assumes
//            that vertices of graph are inherited from CvGraphWeightedVtx.
//      weight_edge - optional matrix of floats, of width and height = graph->total.
//            If weight_type is either CV_WEIGHTED_EDGE or CV_WEIGHTED_ALL
//            weights of edges ought to be supplied.  If weight_edge is not zero
//            function finds them here, otherwise function expects
//            edges of graph to be inherited from CvGraphWeightedEdge.
//            Note that in case of CV_WEIGHTED_EDGE or CV_WEIGHTED_ALL
//            nonzero is_complementary implies nonzero weight_edge.
//      start_clique - optional sequence of pairwise different ints.  They are indices of
//            vertices that shall be present in the output clique.
//      subgraph_of_ban - optional sequence of (maybe equal) ints.  They are indices of
//            vertices that shall not be present in the output clique.
//      clique_weight_ptr - optional output parameter.  Weight of found clique stored here.
//      num_generations - optional number of generations in evolutionary part of algorithm,
//            zero forces to return first found clique.
//      quality - optional parameter determining degree of required quality/speed tradeoff.
//            Must be in the range from 0 to 9.
//            0 is fast and dirty, 9 is slow but hopefully yields good clique.
//    Returns:
//      sequence of pairwise different ints.
//      These are indices of vertices that form found clique.
//    Notes:
//      in cases of CV_WEIGHTED_EDGE and CV_WEIGHTED_ALL weights should be nonnegative.
//      start_clique has a priority over subgraph_of_ban.
//F*/
/*CVAPI(CvSeq*) cvFindCliqueEx( CvGraph *graph, CvMemStorage *storage,
                                 int is_complementary CV_DEFAULT(0),
                                 CvGraphWeightType weight_type CV_DEFAULT(CV_NOT_WEIGHTED),
                                 CvVect32f weight_vtx CV_DEFAULT(0),
                                 CvMatr32f weight_edge CV_DEFAULT(0),
                                 CvSeq *start_clique CV_DEFAULT(0),
                                 CvSeq *subgraph_of_ban CV_DEFAULT(0),
                                 float *clique_weight_ptr CV_DEFAULT(0),
                                 int num_generations CV_DEFAULT(3),
                                 int quality CV_DEFAULT(2) );*/

#define CV_UNDEF_SC_PARAM         12345 //default value of parameters

#define CV_IDP_BIRCHFIELD_PARAM1  25    
#define CV_IDP_BIRCHFIELD_PARAM2  5
#define CV_IDP_BIRCHFIELD_PARAM3  12
#define CV_IDP_BIRCHFIELD_PARAM4  15
#define CV_IDP_BIRCHFIELD_PARAM5  25

#define  CV_DISPARITY_BIRCHFIELD  0

/*F///////////////////////////////////////////////////////////////////////////
//
//    Name:    cvFindStereoCorrespondence
//    Purpose: find stereo correspondence on stereo-pair
//    Context:
//    Parameters:
//      leftImage - left image of stereo-pair (format 8uC1).
//      rightImage - right image of stereo-pair (format 8uC1).
//   mode - mode of correspondence retrieval (now CV_DISPARITY_BIRCHFIELD only)
//      dispImage - destination disparity image
//      maxDisparity - maximal disparity 
//      param1, param2, param3, param4, param5 - parameters of algorithm
//    Returns:
//    Notes:
//      Images must be rectified.
//      All images must have format 8uC1.
//F*/
CVAPI(void) 
cvFindStereoCorrespondence( 
                   const  CvArr* leftImage, const  CvArr* rightImage,
                   int     mode,
                   CvArr*  dispImage,
                   int     maxDisparity,                                
                   double  param1 CV_DEFAULT(CV_UNDEF_SC_PARAM), 
                   double  param2 CV_DEFAULT(CV_UNDEF_SC_PARAM), 
                   double  param3 CV_DEFAULT(CV_UNDEF_SC_PARAM), 
                   double  param4 CV_DEFAULT(CV_UNDEF_SC_PARAM), 
                   double  param5 CV_DEFAULT(CV_UNDEF_SC_PARAM) );

/*****************************************************************************************/
/************ Epiline functions *******************/

typedef struct CvStereoLineCoeff
{
    double Xcoef;
    double XcoefA;
    double XcoefB;
    double XcoefAB;

double Ycoef;
    double YcoefA;
    double YcoefB;
    double YcoefAB;

double Zcoef;
    double ZcoefA;
    double ZcoefB;
    double ZcoefAB;
}CvStereoLineCoeff;

typedef struct CvCamera
{
    float   imgSize[2]; /* size of the camera view, used during calibration */
    float   matrix[9]; /* intinsic camera parameters:  [ fx 0 cx; 0 fy cy; 0 0 1 ] */
    float   distortion[4]; /* distortion coefficients - two coefficients for radial distortion
                              and another two for tangential: [ k1 k2 p1 p2 ] */
    float   rotMatr[9];
    float   transVect[3]; /* rotation matrix and transition vector relatively
                             to some reference point in the space. */
}
CvCamera;

typedef struct CvStereoCamera
{
    CvCamera* camera[2]; /* two individual camera parameters */
    float fundMatr[9]; /* fundamental matrix */

/* New part for stereo */
    CvPoint3D32f epipole[2];
    CvPoint2D32f quad[2][4]; /* coordinates of destination quadrangle after
                                epipolar geometry rectification */
    double coeffs[2][3][3];/* coefficients for transformation */
    CvPoint2D32f border[2][4];
    CvSize warpSize;
    CvStereoLineCoeff* lineCoeffs;
    int needSwapCameras;/* flag set to 1 if need to swap cameras for good reconstruction */
    float rotMatrix[9];
    float transVector[3];
}
CvStereoCamera;

typedef struct CvContourOrientation
{
    float egvals[2];
    float egvects[4];

float max, min; // minimum and maximum projections
    int imax, imin;
} CvContourOrientation;

#define CV_CAMERA_TO_WARP 1
#define CV_WARP_TO_CAMERA 2

CVAPI(int) icvConvertWarpCoordinates(double coeffs[3][3],
                                CvPoint2D32f* cameraPoint,
                                CvPoint2D32f* warpPoint,
                                int direction);

CVAPI(int) icvGetSymPoint3D(  CvPoint3D64f pointCorner,
                            CvPoint3D64f point1,
                            CvPoint3D64f point2,
                            CvPoint3D64f *pointSym2);

CVAPI(void) icvGetPieceLength3D(CvPoint3D64f point1,CvPoint3D64f point2,double* dist);

CVAPI(int) icvCompute3DPoint(    double alpha,double betta,
                            CvStereoLineCoeff* coeffs,
                            CvPoint3D64f* point);

CVAPI(int) icvCreateConvertMatrVect( CvMatr64d     rotMatr1,
                                CvMatr64d     transVect1,
                                CvMatr64d     rotMatr2,
                                CvMatr64d     transVect2,
                                CvMatr64d     convRotMatr,
                                CvMatr64d     convTransVect);

CVAPI(int) icvConvertPointSystem(CvPoint3D64f  M2,
                            CvPoint3D64f* M1,
                            CvMatr64d     rotMatr,
                            CvMatr64d     transVect
                            );

CVAPI(int) icvComputeCoeffForStereo(  CvStereoCamera* stereoCamera);

CVAPI(int) icvGetCrossPieceVector(CvPoint2D32f p1_start,CvPoint2D32f p1_end,CvPoint2D32f v2_start,CvPoint2D32f v2_end,CvPoint2D32f *cross);
CVAPI(int) icvGetCrossLineDirect(CvPoint2D32f p1,CvPoint2D32f p2,float a,float b,float c,CvPoint2D32f* cross);
CVAPI(float) icvDefinePointPosition(CvPoint2D32f point1,CvPoint2D32f point2,CvPoint2D32f point);
CVAPI(int) icvStereoCalibration( int numImages,
                            int* nums,
                            CvSize imageSize,
                            CvPoint2D32f* imagePoints1,
                            CvPoint2D32f* imagePoints2,
                            CvPoint3D32f* objectPoints,
                            CvStereoCamera* stereoparams
                           );

CVAPI(int) icvComputeRestStereoParams(CvStereoCamera *stereoparams);

CVAPI(void) cvComputePerspectiveMap( const double coeffs[3][3], CvArr* rectMapX, CvArr* rectMapY );

CVAPI(int) icvComCoeffForLine(   CvPoint2D64f point1,
                            CvPoint2D64f point2,
                            CvPoint2D64f point3,
                            CvPoint2D64f point4,
                            CvMatr64d    camMatr1,
                            CvMatr64d    rotMatr1,
                            CvMatr64d    transVect1,
                            CvMatr64d    camMatr2,
                            CvMatr64d    rotMatr2,
                            CvMatr64d    transVect2,
                            CvStereoLineCoeff*    coeffs,
                            int* needSwapCameras);

CVAPI(int) icvGetDirectionForPoint(  CvPoint2D64f point,
                                CvMatr64d camMatr,
                                CvPoint3D64f* direct);

CVAPI(int) icvGetCrossLines(CvPoint3D64f point11,CvPoint3D64f point12,
                       CvPoint3D64f point21,CvPoint3D64f point22,
                       CvPoint3D64f* midPoint);

CVAPI(int) icvComputeStereoLineCoeffs(   CvPoint3D64f pointA,
                                    CvPoint3D64f pointB,
                                    CvPoint3D64f pointCam1,
                                    double gamma,
                                    CvStereoLineCoeff*    coeffs);

/*CVAPI(int) icvComputeFundMatrEpipoles ( CvMatr64d camMatr1, 
                                    CvMatr64d     rotMatr1, 
                                    CvVect64d     transVect1,
                                    CvMatr64d     camMatr2,
                                    CvMatr64d     rotMatr2,
                                    CvVect64d     transVect2,
                                    CvPoint2D64f* epipole1,
                                    CvPoint2D64f* epipole2,
                                    CvMatr64d     fundMatr);*/

CVAPI(int) icvGetAngleLine( CvPoint2D64f startPoint, CvSize imageSize,CvPoint2D64f *point1,CvPoint2D64f *point2);

CVAPI(void) icvGetCoefForPiece(   CvPoint2D64f p_start,CvPoint2D64f p_end,
                        double *a,double *b,double *c,
                        int* result);

/*CVAPI(void) icvGetCommonArea( CvSize imageSize,
                    CvPoint2D64f epipole1,CvPoint2D64f epipole2,
                    CvMatr64d fundMatr,
                    CvVect64d coeff11,CvVect64d coeff12,
                    CvVect64d coeff21,CvVect64d coeff22,
                    int* result);*/

CVAPI(void) icvComputeeInfiniteProject1(CvMatr64d    rotMatr,
                                     CvMatr64d    camMatr1,
                                     CvMatr64d    camMatr2,
                                     CvPoint2D32f point1,
                                     CvPoint2D32f *point2);

CVAPI(void) icvComputeeInfiniteProject2(CvMatr64d    rotMatr,
                                     CvMatr64d    camMatr1,
                                     CvMatr64d    camMatr2,
                                     CvPoint2D32f* point1,
                                     CvPoint2D32f point2);

CVAPI(void) icvGetCrossDirectDirect(  CvVect64d direct1,CvVect64d direct2,
                            CvPoint2D64f *cross,int* result);

CVAPI(void) icvGetCrossPieceDirect(   CvPoint2D64f p_start,CvPoint2D64f p_end,
                            double a,double b,double c,
                            CvPoint2D64f *cross,int* result);

CVAPI(void) icvGetCrossPiecePiece( CvPoint2D64f p1_start,CvPoint2D64f p1_end,
                            CvPoint2D64f p2_start,CvPoint2D64f p2_end,
                            CvPoint2D64f* cross,
                            int* result);
                            
CVAPI(void) icvGetPieceLength(CvPoint2D64f point1,CvPoint2D64f point2,double* dist);

CVAPI(void) icvGetCrossRectDirect(    CvSize imageSize,
                            double a,double b,double c,
                            CvPoint2D64f *start,CvPoint2D64f *end,
                            int* result);

CVAPI(void) icvProjectPointToImage(   CvPoint3D64f point,
                            CvMatr64d camMatr,CvMatr64d rotMatr,CvVect64d transVect,
                            CvPoint2D64f* projPoint);

CVAPI(void) icvGetQuadsTransform( CvSize        imageSize,
                        CvMatr64d     camMatr1,
                        CvMatr64d     rotMatr1,
                        CvVect64d     transVect1,
                        CvMatr64d     camMatr2,
                        CvMatr64d     rotMatr2,
                        CvVect64d     transVect2,
                        CvSize*       warpSize,
                        double quad1[4][2],
                        double quad2[4][2],
                        CvMatr64d     fundMatr,
                        CvPoint3D64f* epipole1,
                        CvPoint3D64f* epipole2
                        );

CVAPI(void) icvGetQuadsTransformStruct(  CvStereoCamera* stereoCamera);

CVAPI(void) icvComputeStereoParamsForCameras(CvStereoCamera* stereoCamera);

CVAPI(void) icvGetCutPiece(   CvVect64d areaLineCoef1,CvVect64d areaLineCoef2,
                    CvPoint2D64f epipole,
                    CvSize imageSize,
                    CvPoint2D64f* point11,CvPoint2D64f* point12,
                    CvPoint2D64f* point21,CvPoint2D64f* point22,
                    int* result);

CVAPI(void) icvGetMiddleAnglePoint(   CvPoint2D64f basePoint,
                            CvPoint2D64f point1,CvPoint2D64f point2,
                            CvPoint2D64f* midPoint);

CVAPI(void) icvGetNormalDirect(CvVect64d direct,CvPoint2D64f point,CvVect64d normDirect);

CVAPI(double) icvGetVect(CvPoint2D64f basePoint,CvPoint2D64f point1,CvPoint2D64f point2);

CVAPI(void) icvProjectPointToDirect(  CvPoint2D64f point,CvVect64d lineCoeff,
                            CvPoint2D64f* projectPoint);

CVAPI(void) icvGetDistanceFromPointToDirect( CvPoint2D64f point,CvVect64d lineCoef,double*dist);

CVAPI(IplImage*) icvCreateIsometricImage( IplImage* src, IplImage* dst,
                              int desired_depth, int desired_num_channels );

CVAPI(void) cvDeInterlace( const CvArr* frame, CvArr* fieldEven, CvArr* fieldOdd );

/*CVAPI(int) icvSelectBestRt(           int           numImages,
                                    int*          numPoints,
                                    CvSize        imageSize,
                                    CvPoint2D32f* imagePoints1,
                                    CvPoint2D32f* imagePoints2,
                                    CvPoint3D32f* objectPoints,

CvMatr32f     cameraMatrix1,
                                    CvVect32f     distortion1,
                                    CvMatr32f     rotMatrs1,
                                    CvVect32f     transVects1,

CvMatr32f     cameraMatrix2,
                                    CvVect32f     distortion2,
                                    CvMatr32f     rotMatrs2,
                                    CvVect32f     transVects2,

CvMatr32f     bestRotMatr,
                                    CvVect32f     bestTransVect
                                    );*/

/****************************************************************************************\
*                                   Contour Morphing                                     *
\****************************************************************************************/

/* finds correspondence between two contours */
CvSeq* cvCalcContoursCorrespondence( const CvSeq* contour1,
                                     const CvSeq* contour2, 
                                     CvMemStorage* storage);

/* morphs contours using the pre-calculated correspondence:
   alpha=0 ~ contour1, alpha=1 ~ contour2 */
CvSeq* cvMorphContours( const CvSeq* contour1, const CvSeq* contour2,
                        CvSeq* corr, double alpha,
                        CvMemStorage* storage );

/****************************************************************************************\
*                                    Texture Descriptors                                 *
\****************************************************************************************/

#define CV_GLCM_OPTIMIZATION_NONE                   -2
#define CV_GLCM_OPTIMIZATION_LUT                    -1
#define CV_GLCM_OPTIMIZATION_HISTOGRAM              0

#define CV_GLCMDESC_OPTIMIZATION_ALLOWDOUBLENEST    10
#define CV_GLCMDESC_OPTIMIZATION_ALLOWTRIPLENEST    11
#define CV_GLCMDESC_OPTIMIZATION_HISTOGRAM          4

#define CV_GLCMDESC_ENTROPY                         0
#define CV_GLCMDESC_ENERGY                          1
#define CV_GLCMDESC_HOMOGENITY                      2
#define CV_GLCMDESC_CONTRAST                        3
#define CV_GLCMDESC_CLUSTERTENDENCY                 4
#define CV_GLCMDESC_CLUSTERSHADE                    5
#define CV_GLCMDESC_CORRELATION                     6
#define CV_GLCMDESC_CORRELATIONINFO1                7
#define CV_GLCMDESC_CORRELATIONINFO2                8
#define CV_GLCMDESC_MAXIMUMPROBABILITY              9

#define CV_GLCM_ALL                                 0
#define CV_GLCM_GLCM                                1
#define CV_GLCM_DESC                                2

typedef struct CvGLCM CvGLCM;

CVAPI(CvGLCM*) cvCreateGLCM( const IplImage* srcImage,
                                int stepMagnitude,
                                const int* stepDirections CV_DEFAULT(0),
                                int numStepDirections CV_DEFAULT(0),
                                int optimizationType CV_DEFAULT(CV_GLCM_OPTIMIZATION_NONE));

CVAPI(void) cvReleaseGLCM( CvGLCM** GLCM, int flag CV_DEFAULT(CV_GLCM_ALL));

CVAPI(void) cvCreateGLCMDescriptors( CvGLCM* destGLCM,
                                        int descriptorOptimizationType
                                        CV_DEFAULT(CV_GLCMDESC_OPTIMIZATION_ALLOWDOUBLENEST));

CVAPI(double) cvGetGLCMDescriptor( CvGLCM* GLCM, int step, int descriptor );

CVAPI(void) cvGetGLCMDescriptorStatistics( CvGLCM* GLCM, int descriptor,
                                              double* average, double* standardDeviation );

CVAPI(IplImage*) cvCreateGLCMImage( CvGLCM* GLCM, int step );

/****************************************************************************************\
*                                  Face eyes&mouth tracking                              *
\****************************************************************************************/

typedef struct CvFaceTracker CvFaceTracker;

#define CV_NUM_FACE_ELEMENTS    3 
enum CV_FACE_ELEMENTS
{
    CV_FACE_MOUTH = 0,
    CV_FACE_LEFT_EYE = 1,
    CV_FACE_RIGHT_EYE = 2
};

CVAPI(CvFaceTracker*) cvInitFaceTracker(CvFaceTracker* pFaceTracking, const IplImage* imgGray,
                                                CvRect* pRects, int nRects);
CVAPI(int) cvTrackFace( CvFaceTracker* pFaceTracker, IplImage* imgGray,
                              CvRect* pRects, int nRects,
                              CvPoint* ptRotate, double* dbAngleRotate);
CVAPI(void) cvReleaseFaceTracker(CvFaceTracker** ppFaceTracker);

typedef struct CvFace
{
    CvRect MouthRect;
    CvRect LeftEyeRect;
    CvRect RightEyeRect;
} CvFaceData;

CvSeq * cvFindFace(IplImage * Image,CvMemStorage* storage);
CvSeq * cvPostBoostingFindFace(IplImage * Image,CvMemStorage* storage);

/****************************************************************************************\
*                                         3D Tracker                                     *
\****************************************************************************************/

typedef unsigned char CvBool;

typedef struct
{
    int id;
    CvPoint2D32f p; // pgruebele: So we do not loose precision, this needs to be float
} Cv3dTracker2dTrackedObject;

CV_INLINE Cv3dTracker2dTrackedObject cv3dTracker2dTrackedObject(int id, CvPoint2D32f p)
{
    Cv3dTracker2dTrackedObject r;
    r.id = id;
    r.p = p;
    return r;
}

typedef struct
{
    int id;
    CvPoint3D32f p;             // location of the tracked object
} Cv3dTrackerTrackedObject;

CV_INLINE Cv3dTrackerTrackedObject cv3dTrackerTrackedObject(int id, CvPoint3D32f p)
{
    Cv3dTrackerTrackedObject r;
    r.id = id;
    r.p = p;
    return r;
}

typedef struct
{
    CvBool valid;
    float mat[4][4];              /* maps camera coordinates to world coordinates */
    CvPoint2D32f principal_point; /* copied from intrinsics so this structure */
                                  /* has all the info we need */
} Cv3dTrackerCameraInfo;

typedef struct
{
    CvPoint2D32f principal_point;
    float focal_length[2];
    float distortion[4];
} Cv3dTrackerCameraIntrinsics;

CVAPI(CvBool) cv3dTrackerCalibrateCameras(int num_cameras,
                     const Cv3dTrackerCameraIntrinsics camera_intrinsics[], /* size is num_cameras */
                     CvSize etalon_size,
                     float square_size,
                     IplImage *samples[],                                   /* size is num_cameras */
                     Cv3dTrackerCameraInfo camera_info[]);                  /* size is num_cameras */

CVAPI(int)  cv3dTrackerLocateObjects(int num_cameras, int num_objects,
                   const Cv3dTrackerCameraInfo camera_info[],        /* size is num_cameras */
                   const Cv3dTracker2dTrackedObject tracking_info[], /* size is num_objects*num_cameras */
                   Cv3dTrackerTrackedObject tracked_objects[]);      /* size is num_objects */
/****************************************************************************************
 tracking_info is a rectangular array; one row per camera, num_objects elements per row.
 The id field of any unused slots must be -1. Ids need not be ordered or consecutive. On
 completion, the return value is the number of objects located; i.e., the number of objects
 visible by more than one camera. The id field of any unused slots in tracked objects is
 set to -1.
****************************************************************************************/

/****************************************************************************************\
*                           Skeletons and Linear-Contour Models                          *
\****************************************************************************************/

typedef enum CvLeeParameters
{
    CV_LEE_INT = 0,
    CV_LEE_FLOAT = 1,
    CV_LEE_DOUBLE = 2,
    CV_LEE_AUTO = -1,
    CV_LEE_ERODE = 0,
    CV_LEE_ZOOM = 1,
    CV_LEE_NON = 2
} CvLeeParameters;

#define CV_NEXT_VORONOISITE2D( SITE ) ((SITE)->edge[0]->site[((SITE)->edge[0]->site[0] == (SITE))])
#define CV_PREV_VORONOISITE2D( SITE ) ((SITE)->edge[1]->site[((SITE)->edge[1]->site[0] == (SITE))])
#define CV_FIRST_VORONOIEDGE2D( SITE ) ((SITE)->edge[0])
#define CV_LAST_VORONOIEDGE2D( SITE ) ((SITE)->edge[1])
#define CV_NEXT_VORONOIEDGE2D( EDGE, SITE ) ((EDGE)->next[(EDGE)->site[0] != (SITE)])
#define CV_PREV_VORONOIEDGE2D( EDGE, SITE ) ((EDGE)->next[2 + ((EDGE)->site[0] != (SITE))])
#define CV_VORONOIEDGE2D_BEGINNODE( EDGE, SITE ) ((EDGE)->node[((EDGE)->site[0] != (SITE))])
#define CV_VORONOIEDGE2D_ENDNODE( EDGE, SITE ) ((EDGE)->node[((EDGE)->site[0] == (SITE))])
#define CV_TWIN_VORONOISITE2D( SITE, EDGE ) ( (EDGE)->site[((EDGE)->site[0] == (SITE))])

#define CV_VORONOISITE2D_FIELDS()    \
    struct CvVoronoiNode2D *node[2]; \
    struct CvVoronoiEdge2D *edge[2];

typedef struct CvVoronoiSite2D
{
    CV_VORONOISITE2D_FIELDS()
    struct CvVoronoiSite2D *next[2];
} CvVoronoiSite2D;

#define CV_VORONOIEDGE2D_FIELDS()    \
    struct CvVoronoiNode2D *node[2]; \
    struct CvVoronoiSite2D *site[2]; \
    struct CvVoronoiEdge2D *next[4];

typedef struct CvVoronoiEdge2D
{
    CV_VORONOIEDGE2D_FIELDS()
} CvVoronoiEdge2D;

#define CV_VORONOINODE2D_FIELDS()       \
    CV_SET_ELEM_FIELDS(CvVoronoiNode2D) \
    CvPoint2D32f pt;                    \
    float radius;

typedef struct CvVoronoiNode2D
{
    CV_VORONOINODE2D_FIELDS()
} CvVoronoiNode2D;

#define CV_VORONOIDIAGRAM2D_FIELDS() \
    CV_GRAPH_FIELDS()                \
    CvSet *sites;

typedef struct CvVoronoiDiagram2D
{
    CV_VORONOIDIAGRAM2D_FIELDS()
} CvVoronoiDiagram2D;

/* Computes Voronoi Diagram for given polygons with holes */
CVAPI(int)  cvVoronoiDiagramFromContour(CvSeq* ContourSeq,
                                           CvVoronoiDiagram2D** VoronoiDiagram,
                                           CvMemStorage* VoronoiStorage,
                                           CvLeeParameters contour_type CV_DEFAULT(CV_LEE_INT),
                                           int contour_orientation CV_DEFAULT(-1),
                                           int attempt_number CV_DEFAULT(10));

/* Computes Voronoi Diagram for domains in given image */
CVAPI(int)  cvVoronoiDiagramFromImage(IplImage* pImage,
                                         CvSeq** ContourSeq,
                                         CvVoronoiDiagram2D** VoronoiDiagram,
                                         CvMemStorage* VoronoiStorage,
                                         CvLeeParameters regularization_method CV_DEFAULT(CV_LEE_NON),
                                         float approx_precision CV_DEFAULT(CV_LEE_AUTO));

/* Deallocates the storage */
CVAPI(void) cvReleaseVoronoiStorage(CvVoronoiDiagram2D* VoronoiDiagram,
                                          CvMemStorage** pVoronoiStorage);

/*********************** Linear-Contour Model ****************************/

struct CvLCMEdge;
struct CvLCMNode;

typedef struct CvLCMEdge
{
    CV_GRAPH_EDGE_FIELDS() 
    CvSeq* chain;
    float width;
    int index1;
    int index2;
} CvLCMEdge;

typedef struct CvLCMNode
{
    CV_GRAPH_VERTEX_FIELDS()
    CvContour* contour; 
} CvLCMNode;

/* Computes hybrid model from Voronoi Diagram */
CVAPI(CvGraph*) cvLinearContorModelFromVoronoiDiagram(CvVoronoiDiagram2D* VoronoiDiagram,
                                                         float maxWidth);

/* Releases hybrid model storage */
CVAPI(int) cvReleaseLinearContorModelStorage(CvGraph** Graph);

/* two stereo-related functions */

CVAPI(void) cvInitPerspectiveTransform( CvSize size, const CvPoint2D32f vertex[4], double matrix[3][3],
                                              CvArr* rectMap );

/*CVAPI(void) cvInitStereoRectification( CvStereoCamera* params,
                                             CvArr* rectMap1, CvArr* rectMap2,
                                             int do_undistortion );*/

/*************************** View Morphing Functions ************************/

/* The order of the function corresponds to the order they should appear in
   the view morphing pipeline */

/* Finds ending points of scanlines on left and right images of stereo-pair */
CVAPI(void)  cvMakeScanlines( const CvMatrix3* matrix, CvSize  img_size,
                              int*  scanlines1, int*  scanlines2,
                              int*  lengths1, int*  lengths2,
                              int*  line_count );

/* Grab pixel values from scanlines and stores them sequentially
   (some sort of perspective image transform) */
CVAPI(void)  cvPreWarpImage( int       line_count,
                             IplImage* img,
                             uchar*    dst,
                             int*      dst_nums,
                             int*      scanlines);

/* Approximate each grabbed scanline by a sequence of runs
   (lossy run-length compression) */
CVAPI(void)  cvFindRuns( int    line_count,
                         uchar* prewarp1,
                         uchar* prewarp2,
                         int*   line_lengths1,
                         int*   line_lengths2,
                         int*   runs1,
                         int*   runs2,
                         int*   num_runs1,
                         int*   num_runs2);

/* Compares two sets of compressed scanlines */
CVAPI(void)  cvDynamicCorrespondMulti( int  line_count,
                                       int* first,
                                       int* first_runs,
                                       int* second,
                                       int* second_runs,
                                       int* first_corr,
                                       int* second_corr);

/* Finds scanline ending coordinates for some intermediate "virtual" camera position */
CVAPI(void)  cvMakeAlphaScanlines( int*  scanlines1,
                                   int*  scanlines2,
                                   int*  scanlinesA,
                                   int*  lengths,
                                   int   line_count,
                                   float alpha);

/* Blends data of the left and right image scanlines to get
   pixel values of "virtual" image scanlines */
CVAPI(void)  cvMorphEpilinesMulti( int    line_count,
                                   uchar* first_pix,
                                   int*   first_num,
                                   uchar* second_pix,
                                   int*   second_num,
                                   uchar* dst_pix,
                                   int*   dst_num,
                                   float  alpha,
                                   int*   first,
                                   int*   first_runs,
                                   int*   second,
                                   int*   second_runs,
                                   int*   first_corr,
                                   int*   second_corr);

/* Does reverse warping of the morphing result to make
   it fill the destination image rectangle */
CVAPI(void)  cvPostWarpImage( int       line_count,
                              uchar*    src,
                              int*      src_nums,
                              IplImage* img,
                              int*      scanlines);

/* Deletes Moire (missed pixels that appear due to discretization) */
CVAPI(void)  cvDeleteMoire( IplImage*  img );

/****************************************************************************************\
*                           Background/foreground segmentation                           *
\****************************************************************************************/

/* We discriminate between foreground and background pixels
 * by building and maintaining a model of the background.
 * Any pixel which does not fit this model is then deemed
 * to be foreground.
 *
 * At present we support two core background models,
 * one of which has two variations:
 *
 *  o CV_BG_MODEL_FGD: latest and greatest algorithm, described in
 *    
 *	 Foreground Object Detection from Videos Containing Complex Background.
 *	 Liyuan Li, Weimin Huang, Irene Y.H. Gu, and Qi Tian. 
 *	 ACM MM2003 9p
 *
 *  o CV_BG_MODEL_FGD_SIMPLE:
 *       A code comment describes this as a simplified version of the above,
 *       but the code is in fact currently identical
 *
 *  o CV_BG_MODEL_MOG: "Mixture of Gaussians", older algorithm, described in
 *
 *       Moving target classification and tracking from real-time video.
 *       A Lipton, H Fujijoshi, R Patil
 *       Proceedings IEEE Workshop on Application of Computer Vision pp 8-14 1998
 *
 *       Learning patterns of activity using real-time tracking
 *       C Stauffer and W Grimson  August 2000
 *       IEEE Transactions on Pattern Analysis and Machine Intelligence 22(8):747-757
 */

#define CV_BG_MODEL_FGD		0
#define CV_BG_MODEL_MOG		1			/* "Mixture of Gaussians".	*/
#define CV_BG_MODEL_FGD_SIMPLE	2

struct CvBGStatModel;

typedef void (CV_CDECL * CvReleaseBGStatModel)( struct CvBGStatModel** bg_model );
typedef int (CV_CDECL * CvUpdateBGStatModel)( IplImage* curr_frame, struct CvBGStatModel* bg_model );

#define CV_BG_STAT_MODEL_FIELDS()                                                   \
    int             type; /*type of BG model*/                                      \
    CvReleaseBGStatModel release;                                                   \
    CvUpdateBGStatModel update;                                                     \
    IplImage*       background;   /*8UC3 reference background image*/               \
    IplImage*       foreground;   /*8UC1 foreground image*/                         \
    IplImage**      layers;       /*8UC3 reference background image, can be null */ \
    int             layer_count;  /* can be zero */                                 \
    CvMemStorage*   storage;      /*storage for �foreground_regions�*/              \
    CvSeq*          foreground_regions /*foreground object contours*/

typedef struct CvBGStatModel
{
    CV_BG_STAT_MODEL_FIELDS();
}
CvBGStatModel;

// Releases memory used by BGStatModel
CV_INLINE void cvReleaseBGStatModel( CvBGStatModel** bg_model )
{
    if( bg_model && *bg_model && (*bg_model)->release )
        (*bg_model)->release( bg_model );
}

// Updates statistical model and returns number of found foreground regions
CV_INLINE int cvUpdateBGStatModel( IplImage* current_frame, CvBGStatModel*  bg_model )
{
    return bg_model && bg_model->update ? bg_model->update( current_frame, bg_model ) : 0;
}

// Performs FG post-processing using segmentation
// (all pixels of a region will be classified as foreground if majority of pixels of the region are FG).
// parameters:
//      segments - pointer to result of segmentation (for example MeanShiftSegmentation)
//      bg_model - pointer to CvBGStatModel structure
CVAPI(void) cvRefineForegroundMaskBySegm( CvSeq* segments, CvBGStatModel*  bg_model );

/* Common use change detection function */
CVAPI(int)  cvChangeDetection( IplImage*  prev_frame,
                               IplImage*  curr_frame,
                               IplImage*  change_mask );

/*
  Interface of ACM MM2003 algorithm
*/

/* Default parameters of foreground detection algorithm: */
#define  CV_BGFG_FGD_LC              128
#define  CV_BGFG_FGD_N1C             15
#define  CV_BGFG_FGD_N2C             25

#define  CV_BGFG_FGD_LCC             64
#define  CV_BGFG_FGD_N1CC            25
#define  CV_BGFG_FGD_N2CC            40

/* Background reference image update parameter: */
#define  CV_BGFG_FGD_ALPHA_1         0.1f

/* stat model update parameter
 * 0.002f ~ 1K frame(~45sec), 0.005 ~ 18sec (if 25fps and absolutely static BG)
 */
#define  CV_BGFG_FGD_ALPHA_2         0.005f

/* start value for alpha parameter (to fast initiate statistic model) */
#define  CV_BGFG_FGD_ALPHA_3         0.1f

#define  CV_BGFG_FGD_DELTA           2

#define  CV_BGFG_FGD_T               0.9f

#define  CV_BGFG_FGD_MINAREA         15.f

#define  CV_BGFG_FGD_BG_UPDATE_TRESH 0.5f

/* See the above-referenced Li/Huang/Gu/Tian paper
 * for a full description of these background-model
 * tuning parameters.
 *
 * Nomenclature:  'c'  == "color", a three-component red/green/blue vector.
 *                         We use histograms of these to model the range of
 *                         colors we've seen at a given background pixel.
 *
 *                'cc' == "color co-occurrence", a six-component vector giving
 *                         RGB color for both this frame and preceding frame.
 *                             We use histograms of these to model the range of
 *                         color CHANGES we've seen at a given background pixel.
 */
typedef struct CvFGDStatModelParams
{
    int    Lc;			/* Quantized levels per 'color' component. Power of two, typically 32, 64 or 128.				*/
    int    N1c;			/* Number of color vectors used to model normal background color variation at a given pixel.			*/
    int    N2c;			/* Number of color vectors retained at given pixel.  Must be > N1c, typically ~ 5/3 of N1c.			*/
				/* Used to allow the first N1c vectors to adapt over time to changing background.				*/

int    Lcc;			/* Quantized levels per 'color co-occurrence' component.  Power of two, typically 16, 32 or 64.			*/
    int    N1cc;		/* Number of color co-occurrence vectors used to model normal background color variation at a given pixel.	*/
    int    N2cc;		/* Number of color co-occurrence vectors retained at given pixel.  Must be > N1cc, typically ~ 5/3 of N1cc.	*/
				/* Used to allow the first N1cc vectors to adapt over time to changing background.				*/

int    is_obj_without_holes;/* If TRUE we ignore holes within foreground blobs. Defaults to TRUE.						*/
    int    perform_morphing;	/* Number of erode-dilate-erode foreground-blob cleanup iterations.						*/
				/* These erase one-pixel junk blobs and merge almost-touching blobs. Default value is 1.			*/

float  alpha1;		/* How quickly we forget old background pixel values seen.  Typically set to 0.1  				*/
    float  alpha2;		/* "Controls speed of feature learning". Depends on T. Typical value circa 0.005. 				*/
    float  alpha3;		/* Alternate to alpha2, used (e.g.) for quicker initial convergence. Typical value 0.1.				*/

float  delta;		/* Affects color and color co-occurrence quantization, typically set to 2.					*/
    float  T;			/* "A percentage value which determines when new features can be recognized as new background." (Typically 0.9).*/
    float  minArea;		/* Discard foreground blobs whose bounding box is smaller than this threshold.					*/
}
CvFGDStatModelParams;

typedef struct CvBGPixelCStatTable
{
    float          Pv, Pvb;
    uchar          v[3];
}
CvBGPixelCStatTable;

typedef struct CvBGPixelCCStatTable
{
    float          Pv, Pvb;
    uchar          v[6];
}
CvBGPixelCCStatTable;

typedef struct CvBGPixelStat
{
    float                 Pbc;
    float                 Pbcc;
    CvBGPixelCStatTable*  ctable;
    CvBGPixelCCStatTable* cctable;
    uchar                 is_trained_st_model;
    uchar                 is_trained_dyn_model;
}
CvBGPixelStat;

typedef struct CvFGDStatModel
{
    CV_BG_STAT_MODEL_FIELDS();
    CvBGPixelStat*         pixel_stat;
    IplImage*              Ftd;
    IplImage*              Fbd;
    IplImage*              prev_frame;
    CvFGDStatModelParams   params;
}
CvFGDStatModel;

/* Creates FGD model */
CVAPI(CvBGStatModel*) cvCreateFGDStatModel( IplImage* first_frame,
                    CvFGDStatModelParams* parameters CV_DEFAULT(NULL));

/* 
   Interface of Gaussian mixture algorithm

"An improved adaptive background mixture model for real-time tracking with shadow detection"
   P. KadewTraKuPong and R. Bowden,
   Proc. 2nd European Workshp on Advanced Video-Based Surveillance Systems, 2001."
   http://personal.ee.surrey.ac.uk/Personal/R.Bowden/publications/avbs01/avbs01.pdf
*/

/* Note:  "MOG" == "Mixture Of Gaussians": */

#define CV_BGFG_MOG_MAX_NGAUSSIANS 500

/* default parameters of gaussian background detection algorithm */
#define CV_BGFG_MOG_BACKGROUND_THRESHOLD     0.7     /* threshold sum of weights for background test */
#define CV_BGFG_MOG_STD_THRESHOLD            2.5     /* lambda=2.5 is 99% */
#define CV_BGFG_MOG_WINDOW_SIZE              200     /* Learning rate; alpha = 1/CV_GBG_WINDOW_SIZE */
#define CV_BGFG_MOG_NGAUSSIANS               5       /* = K = number of Gaussians in mixture */
#define CV_BGFG_MOG_WEIGHT_INIT              0.05
#define CV_BGFG_MOG_SIGMA_INIT               30
#define CV_BGFG_MOG_MINAREA                  15.f

#define CV_BGFG_MOG_NCOLORS                  3

typedef struct CvGaussBGStatModelParams
{    
    int     win_size;               /* = 1/alpha */
    int     n_gauss;
    double  bg_threshold, std_threshold, minArea;
    double  weight_init, variance_init;
}CvGaussBGStatModelParams;

typedef struct CvGaussBGValues
{
    int         match_sum;
    double      weight;
    double      variance[CV_BGFG_MOG_NCOLORS];
    double      mean[CV_BGFG_MOG_NCOLORS];
}
CvGaussBGValues;

typedef struct CvGaussBGPoint
{
    CvGaussBGValues* g_values;
}
CvGaussBGPoint;

typedef struct CvGaussBGModel
{
    CV_BG_STAT_MODEL_FIELDS();
    CvGaussBGStatModelParams   params;    
    CvGaussBGPoint*            g_point;    
    int                        countFrames;
}
CvGaussBGModel;

/* Creates Gaussian mixture background model */
CVAPI(CvBGStatModel*) cvCreateGaussianBGModel( IplImage* first_frame,
                CvGaussBGStatModelParams* parameters CV_DEFAULT(NULL));

typedef struct CvBGCodeBookElem
{
    struct CvBGCodeBookElem* next;
    int tLastUpdate;
    int stale;
    uchar boxMin[3];
    uchar boxMax[3];
    uchar learnMin[3];
    uchar learnMax[3];
}
CvBGCodeBookElem;

typedef struct CvBGCodeBookModel
{
    CvSize size;
    int t;
    uchar cbBounds[3];
    uchar modMin[3];
    uchar modMax[3];
    CvBGCodeBookElem** cbmap;
    CvMemStorage* storage;
    CvBGCodeBookElem* freeList;
}
CvBGCodeBookModel;

CVAPI(CvBGCodeBookModel*) cvCreateBGCodeBookModel();
CVAPI(void) cvReleaseBGCodeBookModel( CvBGCodeBookModel** model );

CVAPI(void) cvBGCodeBookUpdate( CvBGCodeBookModel* model, const CvArr* image,
                                CvRect roi CV_DEFAULT(cvRect(0,0,0,0)),
                                const CvArr* mask CV_DEFAULT(0) );

CVAPI(int) cvBGCodeBookDiff( const CvBGCodeBookModel* model, const CvArr* image,
                             CvArr* fgmask, CvRect roi CV_DEFAULT(cvRect(0,0,0,0)) );

CVAPI(void) cvBGCodeBookClearStale( CvBGCodeBookModel* model, int staleThresh,
                                    CvRect roi CV_DEFAULT(cvRect(0,0,0,0)),
                                    const CvArr* mask CV_DEFAULT(0) );

CVAPI(CvSeq*) cvSegmentFGMask( CvArr *fgmask, int poly1Hull0 CV_DEFAULT(1),
                               float perimScale CV_DEFAULT(4.f),
                               CvMemStorage* storage CV_DEFAULT(0),
                               CvPoint offset CV_DEFAULT(cvPoint(0,0)));

#ifdef __cplusplus
}
#endif

#ifdef __cplusplus

/****************************************************************************************\
*                                   Calibration engine                                   *
\****************************************************************************************/

typedef enum CvCalibEtalonType
{
    CV_CALIB_ETALON_USER = -1,
    CV_CALIB_ETALON_CHESSBOARD = 0,
    CV_CALIB_ETALON_CHECKERBOARD = CV_CALIB_ETALON_CHESSBOARD
}
CvCalibEtalonType;

class CV_EXPORTS CvCalibFilter
{
public:
    /* Constructor & destructor */
    CvCalibFilter();
    virtual ~CvCalibFilter();

/* Sets etalon type - one for all cameras.
       etalonParams is used in case of pre-defined etalons (such as chessboard).
       Number of elements in etalonParams is determined by etalonType.
       E.g., if etalon type is CV_ETALON_TYPE_CHESSBOARD then:
         etalonParams[0] is number of squares per one side of etalon
         etalonParams[1] is number of squares per another side of etalon
         etalonParams[2] is linear size of squares in the board in arbitrary units.
       pointCount & points are used in case of
       CV_CALIB_ETALON_USER (user-defined) etalon. */
    virtual bool
        SetEtalon( CvCalibEtalonType etalonType, double* etalonParams,
                   int pointCount = 0, CvPoint2D32f* points = 0 );

/* Retrieves etalon parameters/or and points */
    virtual CvCalibEtalonType
        GetEtalon( int* paramCount = 0, const double** etalonParams = 0,
                   int* pointCount = 0, const CvPoint2D32f** etalonPoints = 0 ) const;

/* Sets number of cameras calibrated simultaneously. It is equal to 1 initially */
    virtual void SetCameraCount( int cameraCount );

/* Retrieves number of cameras */
    int GetCameraCount() const { return cameraCount; }

/* Starts cameras calibration */
    virtual bool SetFrames( int totalFrames );
    
    /* Stops cameras calibration */
    virtual void Stop( bool calibrate = false );

/* Retrieves number of cameras */
    bool IsCalibrated() const { return isCalibrated; }

/* Feeds another serie of snapshots (one per each camera) to filter.
       Etalon points on these images are found automatically.
       If the function can't locate points, it returns false */
    virtual bool FindEtalon( IplImage** imgs );

/* The same but takes matrices */
    virtual bool FindEtalon( CvMat** imgs );

/* Lower-level function for feeding filter with already found etalon points.
       Array of point arrays for each camera is passed. */
    virtual bool Push( const CvPoint2D32f** points = 0 );

/* Returns total number of accepted frames and, optionally,
       total number of frames to collect */
    virtual int GetFrameCount( int* framesTotal = 0 ) const;

/* Retrieves camera parameters for specified camera.
       If camera is not calibrated the function returns 0 */
    virtual const CvCamera* GetCameraParams( int idx = 0 ) const;

virtual const CvStereoCamera* GetStereoParams() const;

/* Sets camera parameters for all cameras */
    virtual bool SetCameraParams( CvCamera* params );

/* Saves all camera parameters to file */
    virtual bool SaveCameraParams( const char* filename );
    
    /* Loads all camera parameters from file */
    virtual bool LoadCameraParams( const char* filename );

/* Undistorts images using camera parameters. Some of src pointers can be NULL. */
    virtual bool Undistort( IplImage** src, IplImage** dst );

/* Undistorts images using camera parameters. Some of src pointers can be NULL. */
    virtual bool Undistort( CvMat** src, CvMat** dst );

/* Returns array of etalon points detected/partally detected
       on the latest frame for idx-th camera */
    virtual bool GetLatestPoints( int idx, CvPoint2D32f** pts,
                                                  int* count, bool* found );

/* Draw the latest detected/partially detected etalon */
    virtual void DrawPoints( IplImage** dst );

/* Draw the latest detected/partially detected etalon */
    virtual void DrawPoints( CvMat** dst );

virtual bool Rectify( IplImage** srcarr, IplImage** dstarr );
    virtual bool Rectify( CvMat** srcarr, CvMat** dstarr );

protected:

enum { MAX_CAMERAS = 3 };

/* etalon data */
    CvCalibEtalonType  etalonType;
    int     etalonParamCount;
    double* etalonParams;
    int     etalonPointCount;
    CvPoint2D32f* etalonPoints;
    CvSize  imgSize;
    CvMat*  grayImg;
    CvMat*  tempImg;
    CvMemStorage* storage;

/* camera data */
    int     cameraCount;
    CvCamera cameraParams[MAX_CAMERAS];
    CvStereoCamera stereo;
    CvPoint2D32f* points[MAX_CAMERAS];
    CvMat*  undistMap[MAX_CAMERAS][2];
    CvMat*  undistImg;
    int     latestCounts[MAX_CAMERAS];
    CvPoint2D32f* latestPoints[MAX_CAMERAS];
    CvMat*  rectMap[MAX_CAMERAS][2];

/* Added by Valery */
    //CvStereoCamera stereoParams;

int     maxPoints;
    int     framesTotal;
    int     framesAccepted;
    bool    isCalibrated;
};

#include "cvaux.hpp"
#include "cvvidsurv.hpp"
/*#include "cvmat.hpp"*/
#endif

#endif

/* End of file. */

C++程序 | 1575行 | 62.41 KB

登录后可以享受更多权益