--- /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*/
+
+#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"
+#endif
+
+#endif
+
+/* End of file. */
projects / opencv / blobdiff