--- /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*/
+#include "_cv.h"
+#include <float.h>
+#include <stdio.h>
+
+namespace cv
+{
+
+void calcOpticalFlowPyrLK( const Mat& prevImg, const Mat& nextImg,
+ const vector<Point2f>& prevPts,
+ vector<Point2f>& nextPts,
+ vector<uchar>& status, vector<float>& err,
+ Size winSize, int maxLevel,
+ TermCriteria criteria,
+ double derivLambda,
+ int flags )
+{
+ derivLambda = std::min(std::max(derivLambda, 0.), 1.);
+ double lambda1 = 1. - derivLambda, lambda2 = derivLambda;
+ const int derivKernelSize = 3;
+ const float deriv1Scale = 0.5f/4.f;
+ const float deriv2Scale = 0.25f/4.f;
+ const int derivDepth = CV_32F;
+ Point2f halfWin((winSize.width-1)*0.5f, (winSize.height-1)*0.5f);
+
+ CV_Assert( maxLevel >= 0 && winSize.width > 2 && winSize.height > 2 );
+ CV_Assert( prevImg.size() == nextImg.size() &&
+ prevImg.type() == nextImg.type() );
+
+ size_t npoints = prevPts.size();
+ nextPts.resize(npoints);
+ status.resize(npoints);
+ for( size_t i = 0; i < npoints; i++ )
+ status[i] = true;
+ err.resize(npoints);
+
+ if( npoints == 0 )
+ return;
+
+ vector<Mat> prevPyr, nextPyr;
+
+ int cn = prevImg.channels();
+ buildPyramid( prevImg, prevPyr, maxLevel );
+ buildPyramid( nextImg, nextPyr, maxLevel );
+ // I, dI/dx ~ Ix, dI/dy ~ Iy, d2I/dx2 ~ Ixx, d2I/dxdy ~ Ixy, d2I/dy2 ~ Iyy
+ Mat derivIBuf((prevImg.rows + winSize.height*2),
+ (prevImg.cols + winSize.width*2),
+ CV_MAKETYPE(derivDepth, cn*6));
+ // J, dJ/dx ~ Jx, dJ/dy ~ Jy
+ Mat derivJBuf((prevImg.rows + winSize.height*2),
+ (prevImg.cols + winSize.width*2),
+ CV_MAKETYPE(derivDepth, cn*3));
+ Mat tempDerivBuf(prevImg.size(), CV_MAKETYPE(derivIBuf.type(), cn));
+ Mat derivIWinBuf(winSize, derivIBuf.type());
+
+ if( (criteria.type & TermCriteria::COUNT) == 0 )
+ criteria.maxCount = 30;
+ else
+ criteria.maxCount = std::min(std::max(criteria.maxCount, 0), 100);
+ if( (criteria.type & TermCriteria::EPS) == 0 )
+ criteria.epsilon = 0.01;
+ else
+ criteria.epsilon = std::min(std::max(criteria.epsilon, 0.), 10.);
+ criteria.epsilon *= criteria.epsilon;
+
+ for( int level = maxLevel; level >= 0; level-- )
+ {
+ int k;
+ Size imgSize = prevPyr[level].size();
+ Mat tempDeriv( imgSize, tempDerivBuf.type(), tempDerivBuf.data );
+ Mat _derivI( imgSize.height + winSize.height*2,
+ imgSize.width + winSize.width*2,
+ derivIBuf.type(), derivIBuf.data );
+ Mat _derivJ( imgSize.height + winSize.height*2,
+ imgSize.width + winSize.width*2,
+ derivJBuf.type(), derivJBuf.data );
+ Mat derivI(_derivI, Rect(winSize.width, winSize.height, imgSize.width, imgSize.height));
+ Mat derivJ(_derivJ, Rect(winSize.width, winSize.height, imgSize.width, imgSize.height));
+ CvMat cvderivI = _derivI;
+ cvZero(&cvderivI);
+ CvMat cvderivJ = _derivJ;
+ cvZero(&cvderivJ);
+
+ vector<int> fromTo(cn*2);
+ for( k = 0; k < cn; k++ )
+ fromTo[k*2] = k;
+
+ prevPyr[level].convertTo(tempDeriv, derivDepth);
+ for( k = 0; k < cn; k++ )
+ fromTo[k*2+1] = k*6;
+ mixChannels(&tempDeriv, 1, &derivI, 1, &fromTo[0], cn);
+
+ // compute spatial derivatives and merge them together
+ Sobel(prevPyr[level], tempDeriv, derivDepth, 1, 0, derivKernelSize, deriv1Scale );
+ for( k = 0; k < cn; k++ )
+ fromTo[k*2+1] = k*6 + 1;
+ mixChannels(&tempDeriv, 1, &derivI, 1, &fromTo[0], cn);
+
+ Sobel(prevPyr[level], tempDeriv, derivDepth, 0, 1, derivKernelSize, deriv1Scale );
+ for( k = 0; k < cn; k++ )
+ fromTo[k*2+1] = k*6 + 2;
+ mixChannels(&tempDeriv, 1, &derivI, 1, &fromTo[0], cn);
+
+ Sobel(prevPyr[level], tempDeriv, derivDepth, 2, 0, derivKernelSize, deriv2Scale );
+ for( k = 0; k < cn; k++ )
+ fromTo[k*2+1] = k*6 + 3;
+ mixChannels(&tempDeriv, 1, &derivI, 1, &fromTo[0], cn);
+
+ Sobel(prevPyr[level], tempDeriv, derivDepth, 1, 1, derivKernelSize, deriv2Scale );
+ for( k = 0; k < cn; k++ )
+ fromTo[k*2+1] = k*6 + 4;
+ mixChannels(&tempDeriv, 1, &derivI, 1, &fromTo[0], cn);
+
+ Sobel(prevPyr[level], tempDeriv, derivDepth, 0, 2, derivKernelSize, deriv2Scale );
+ for( k = 0; k < cn; k++ )
+ fromTo[k*2+1] = k*6 + 5;
+ mixChannels(&tempDeriv, 1, &derivI, 1, &fromTo[0], cn);
+
+ nextPyr[level].convertTo(tempDeriv, derivDepth);
+ for( k = 0; k < cn; k++ )
+ fromTo[k*2+1] = k*3;
+ mixChannels(&tempDeriv, 1, &derivJ, 1, &fromTo[0], cn);
+
+ Sobel(nextPyr[level], tempDeriv, derivDepth, 1, 0, derivKernelSize, deriv1Scale );
+ for( k = 0; k < cn; k++ )
+ fromTo[k*2+1] = k*3 + 1;
+ mixChannels(&tempDeriv, 1, &derivJ, 1, &fromTo[0], cn);
+
+ Sobel(nextPyr[level], tempDeriv, derivDepth, 0, 1, derivKernelSize, deriv1Scale );
+ for( k = 0; k < cn; k++ )
+ fromTo[k*2+1] = k*3 + 2;
+ mixChannels(&tempDeriv, 1, &derivJ, 1, &fromTo[0], cn);
+
+ /*copyMakeBorder( derivI, _derivI, winSize.height, winSize.height,
+ winSize.width, winSize.width, BORDER_CONSTANT );
+ copyMakeBorder( derivJ, _derivJ, winSize.height, winSize.height,
+ winSize.width, winSize.width, BORDER_CONSTANT );*/
+
+ for( size_t ptidx = 0; ptidx < npoints; ptidx++ )
+ {
+ Point2f prevPt = prevPts[ptidx]*(float)(1./(1 << level));
+ Point2f nextPt;
+ if( level == maxLevel )
+ {
+ if( flags & OPTFLOW_USE_INITIAL_FLOW )
+ nextPt = nextPts[ptidx]*(float)(1./(1 << level));
+ else
+ nextPt = prevPt;
+ }
+ else
+ nextPt = nextPts[ptidx]*2.f;
+ nextPts[ptidx] = nextPt;
+
+ Point2i iprevPt, inextPt;
+ prevPt -= halfWin;
+ iprevPt.x = cvFloor(prevPt.x);
+ iprevPt.y = cvFloor(prevPt.y);
+
+ if( iprevPt.x < -winSize.width || iprevPt.x >= derivI.cols ||
+ iprevPt.y < -winSize.height || iprevPt.y >= derivI.rows )
+ {
+ if( level == 0 )
+ {
+ status[ptidx] = false;
+ err[ptidx] = FLT_MAX;
+ }
+ continue;
+ }
+
+ float a = prevPt.x - iprevPt.x;
+ float b = prevPt.y - iprevPt.y;
+ float w00 = (1.f - a)*(1.f - b), w01 = a*(1.f - b);
+ float w10 = (1.f - a)*b, w11 = a*b;
+ size_t stepI = derivI.step/derivI.elemSize1();
+ size_t stepJ = derivJ.step/derivJ.elemSize1();
+ int cnI = cn*6, cnJ = cn*3;
+ double A11 = 0, A12 = 0, A22 = 0;
+ double iA11 = 0, iA12 = 0, iA22 = 0;
+
+ // extract the patch from the first image
+ int x, y;
+ for( y = 0; y < winSize.height; y++ )
+ {
+ const float* src = (const float*)(derivI.data +
+ (y + iprevPt.y)*derivI.step) + iprevPt.x*cnI;
+ float* dst = (float*)(derivIWinBuf.data + y*derivIWinBuf.step);
+
+ for( x = 0; x < winSize.width*cnI; x += cnI, src += cnI )
+ {
+ float I = src[0]*w00 + src[cnI]*w01 + src[stepI]*w10 + src[stepI+cnI]*w11;
+ dst[x] = I;
+
+ float Ix = src[1]*w00 + src[cnI+1]*w01 + src[stepI+1]*w10 + src[stepI+cnI+1]*w11;
+ float Iy = src[2]*w00 + src[cnI+2]*w01 + src[stepI+2]*w10 + src[stepI+cnI+2]*w11;
+ dst[x+1] = Ix; dst[x+2] = Iy;
+
+ float Ixx = src[3]*w00 + src[cnI+3]*w01 + src[stepI+3]*w10 + src[stepI+cnI+3]*w11;
+ float Ixy = src[4]*w00 + src[cnI+4]*w01 + src[stepI+4]*w10 + src[stepI+cnI+4]*w11;
+ float Iyy = src[5]*w00 + src[cnI+5]*w01 + src[stepI+5]*w10 + src[stepI+cnI+5]*w11;
+ dst[x+3] = Ixx; dst[x+4] = Ixy; dst[x+5] = Iyy;
+
+ iA11 += (double)Ix*Ix;
+ iA12 += (double)Ix*Iy;
+ iA22 += (double)Iy*Iy;
+
+ A11 += (double)Ixx*Ixx + (double)Ixy*Ixy;
+ A12 += Ixy*((double)Ixx + Iyy);
+ A22 += (double)Ixy*Ixy + (double)Iyy*Iyy;
+ }
+ }
+
+ A11 = lambda1*iA11 + lambda2*A11;
+ A12 = lambda1*iA12 + lambda2*A12;
+ A22 = lambda1*iA22 + lambda2*A22;
+
+ double D = A11*A22 - A12*A12;
+ double minEig = (A22 + A11 - std::sqrt((A11-A22)*(A11-A22) +
+ 4.*A12*A12))/(2*winSize.width*winSize.height);
+ err[ptidx] = (float)minEig;
+
+ if( D < DBL_EPSILON )
+ {
+ if( level == 0 )
+ status[ptidx] = false;
+ continue;
+ }
+
+ D = 1./D;
+
+ nextPt -= halfWin;
+ Point2f prevDelta;
+
+ for( int j = 0; j < criteria.maxCount; j++ )
+ {
+ inextPt.x = cvFloor(nextPt.x);
+ inextPt.y = cvFloor(nextPt.y);
+
+ if( inextPt.x < -winSize.width || inextPt.x >= derivJ.cols ||
+ inextPt.y < -winSize.height || inextPt.y >= derivJ.rows )
+ {
+ if( level == 0 )
+ status[ptidx] = false;
+ break;
+ }
+
+ a = nextPt.x - inextPt.x;
+ b = nextPt.y - inextPt.y;
+ w00 = (1.f - a)*(1.f - b); w01 = a*(1.f - b);
+ w10 = (1.f - a)*b; w11 = a*b;
+
+ double b1 = 0, b2 = 0, ib1 = 0, ib2 = 0;
+
+ for( y = 0; y < winSize.height; y++ )
+ {
+ const float* src = (const float*)(derivJ.data +
+ (y + inextPt.y)*derivJ.step) + inextPt.x*cnJ;
+ const float* Ibuf = (float*)(derivIWinBuf.data + y*derivIWinBuf.step);
+
+ for( x = 0; x < winSize.width; x++, src += cnJ, Ibuf += cnI )
+ {
+ double It = src[0]*w00 + src[cnJ]*w01 + src[stepJ]*w10 +
+ src[stepJ+cnJ]*w11 - Ibuf[0];
+ double Ixt = src[1]*w00 + src[cnJ+1]*w01 + src[stepJ+1]*w10 +
+ src[stepJ+cnJ+1]*w11 - Ibuf[1];
+ double Iyt = src[2]*w00 + src[cnJ+2]*w01 + src[stepJ+2]*w10 +
+ src[stepJ+cnJ+2]*w11 - Ibuf[2];
+ b1 += Ixt*Ibuf[3] + Iyt*Ibuf[4];
+ b2 += Ixt*Ibuf[4] + Iyt*Ibuf[5];
+ ib1 += It*Ibuf[1];
+ ib2 += It*Ibuf[2];
+ }
+ }
+
+ b1 = lambda1*ib1 + lambda2*b1;
+ b2 = lambda1*ib2 + lambda2*b2;
+ Point2f delta( (float)((A12*b2 - A22*b1) * D),
+ (float)((A12*b1 - A11*b2) * D));
+ //delta = -delta;
+
+ nextPt += delta;
+ nextPts[ptidx] = nextPt + halfWin;
+
+ if( delta.ddot(delta) <= criteria.epsilon )
+ break;
+
+ if( j > 0 && std::abs(delta.x + prevDelta.x) < 0.01 &&
+ std::abs(delta.y + prevDelta.y) < 0.01 )
+ {
+ nextPts[ptidx] -= delta*0.5f;
+ break;
+ }
+ prevDelta = delta;
+ }
+ }
+ }
+}
+
+}
+
+static void
+intersect( CvPoint2D32f pt, CvSize win_size, CvSize imgSize,
+ CvPoint* min_pt, CvPoint* max_pt )
+{
+ CvPoint ipt;
+
+ ipt.x = cvFloor( pt.x );
+ ipt.y = cvFloor( pt.y );
+
+ ipt.x -= win_size.width;
+ ipt.y -= win_size.height;
+
+ win_size.width = win_size.width * 2 + 1;
+ win_size.height = win_size.height * 2 + 1;
+
+ min_pt->x = MAX( 0, -ipt.x );
+ min_pt->y = MAX( 0, -ipt.y );
+ max_pt->x = MIN( win_size.width, imgSize.width - ipt.x );
+ max_pt->y = MIN( win_size.height, imgSize.height - ipt.y );
+}
+
+
+static int icvMinimalPyramidSize( CvSize imgSize )
+{
+ return cvAlign(imgSize.width,8) * imgSize.height / 3;
+}
+
+
+static void
+icvInitPyramidalAlgorithm( const CvMat* imgA, const CvMat* imgB,
+ CvMat* pyrA, CvMat* pyrB,
+ int level, CvTermCriteria * criteria,
+ int max_iters, int flags,
+ uchar *** imgI, uchar *** imgJ,
+ int **step, CvSize** size,
+ double **scale, uchar ** buffer )
+{
+ CV_FUNCNAME( "icvInitPyramidalAlgorithm" );
+
+ __BEGIN__;
+
+ const int ALIGN = 8;
+ int pyrBytes, bufferBytes = 0, elem_size;
+ int level1 = level + 1;
+
+ int i;
+ CvSize imgSize, levelSize;
+
+ *buffer = 0;
+ *imgI = *imgJ = 0;
+ *step = 0;
+ *scale = 0;
+ *size = 0;
+
+ /* check input arguments */
+ if( ((flags & CV_LKFLOW_PYR_A_READY) != 0 && !pyrA) ||
+ ((flags & CV_LKFLOW_PYR_B_READY) != 0 && !pyrB) )
+ CV_ERROR( CV_StsNullPtr, "Some of the precomputed pyramids are missing" );
+
+ if( level < 0 )
+ CV_ERROR( CV_StsOutOfRange, "The number of pyramid layers is negative" );
+
+ switch( criteria->type )
+ {
+ case CV_TERMCRIT_ITER:
+ criteria->epsilon = 0.f;
+ break;
+ case CV_TERMCRIT_EPS:
+ criteria->max_iter = max_iters;
+ break;
+ case CV_TERMCRIT_ITER | CV_TERMCRIT_EPS:
+ break;
+ default:
+ assert( 0 );
+ CV_ERROR( CV_StsBadArg, "Invalid termination criteria" );
+ }
+
+ /* compare squared values */
+ criteria->epsilon *= criteria->epsilon;
+
+ /* set pointers and step for every level */
+ pyrBytes = 0;
+
+ imgSize = cvGetSize(imgA);
+ elem_size = CV_ELEM_SIZE(imgA->type);
+ levelSize = imgSize;
+
+ for( i = 1; i < level1; i++ )
+ {
+ levelSize.width = (levelSize.width + 1) >> 1;
+ levelSize.height = (levelSize.height + 1) >> 1;
+
+ int tstep = cvAlign(levelSize.width,ALIGN) * elem_size;
+ pyrBytes += tstep * levelSize.height;
+ }
+
+ assert( pyrBytes <= imgSize.width * imgSize.height * elem_size * 4 / 3 );
+
+ /* buffer_size = <size for patches> + <size for pyramids> */
+ bufferBytes = (int)((level1 >= 0) * ((pyrA->data.ptr == 0) +
+ (pyrB->data.ptr == 0)) * pyrBytes +
+ (sizeof(imgI[0][0]) * 2 + sizeof(step[0][0]) +
+ sizeof(size[0][0]) + sizeof(scale[0][0])) * level1);
+
+ CV_CALL( *buffer = (uchar *)cvAlloc( bufferBytes ));
+
+ *imgI = (uchar **) buffer[0];
+ *imgJ = *imgI + level1;
+ *step = (int *) (*imgJ + level1);
+ *scale = (double *) (*step + level1);
+ *size = (CvSize *)(*scale + level1);
+
+ imgI[0][0] = imgA->data.ptr;
+ imgJ[0][0] = imgB->data.ptr;
+ step[0][0] = imgA->step;
+ scale[0][0] = 1;
+ size[0][0] = imgSize;
+
+ if( level > 0 )
+ {
+ uchar *bufPtr = (uchar *) (*size + level1);
+ uchar *ptrA = pyrA->data.ptr;
+ uchar *ptrB = pyrB->data.ptr;
+
+ if( !ptrA )
+ {
+ ptrA = bufPtr;
+ bufPtr += pyrBytes;
+ }
+
+ if( !ptrB )
+ ptrB = bufPtr;
+
+ levelSize = imgSize;
+
+ /* build pyramids for both frames */
+ for( i = 1; i <= level; i++ )
+ {
+ int levelBytes;
+ CvMat prev_level, next_level;
+
+ levelSize.width = (levelSize.width + 1) >> 1;
+ levelSize.height = (levelSize.height + 1) >> 1;
+
+ size[0][i] = levelSize;
+ step[0][i] = cvAlign( levelSize.width, ALIGN ) * elem_size;
+ scale[0][i] = scale[0][i - 1] * 0.5;
+
+ levelBytes = step[0][i] * levelSize.height;
+ imgI[0][i] = (uchar *) ptrA;
+ ptrA += levelBytes;
+
+ if( !(flags & CV_LKFLOW_PYR_A_READY) )
+ {
+ prev_level = cvMat( size[0][i-1].height, size[0][i-1].width, CV_8UC1 );
+ next_level = cvMat( size[0][i].height, size[0][i].width, CV_8UC1 );
+ cvSetData( &prev_level, imgI[0][i-1], step[0][i-1] );
+ cvSetData( &next_level, imgI[0][i], step[0][i] );
+ cvPyrDown( &prev_level, &next_level );
+ }
+
+ imgJ[0][i] = (uchar *) ptrB;
+ ptrB += levelBytes;
+
+ if( !(flags & CV_LKFLOW_PYR_B_READY) )
+ {
+ prev_level = cvMat( size[0][i-1].height, size[0][i-1].width, CV_8UC1 );
+ next_level = cvMat( size[0][i].height, size[0][i].width, CV_8UC1 );
+ cvSetData( &prev_level, imgJ[0][i-1], step[0][i-1] );
+ cvSetData( &next_level, imgJ[0][i], step[0][i] );
+ cvPyrDown( &prev_level, &next_level );
+ }
+ }
+ }
+
+ __END__;
+}
+
+
+/* compute dI/dx and dI/dy */
+static void
+icvCalcIxIy_32f( const float* src, int src_step, float* dstX, float* dstY, int dst_step,
+ CvSize src_size, const float* smooth_k, float* buffer0 )
+{
+ int src_width = src_size.width, dst_width = src_size.width-2;
+ int x, height = src_size.height - 2;
+ float* buffer1 = buffer0 + src_width;
+
+ src_step /= sizeof(src[0]);
+ dst_step /= sizeof(dstX[0]);
+
+ for( ; height--; src += src_step, dstX += dst_step, dstY += dst_step )
+ {
+ const float* src2 = src + src_step;
+ const float* src3 = src + src_step*2;
+
+ for( x = 0; x < src_width; x++ )
+ {
+ float t0 = (src3[x] + src[x])*smooth_k[0] + src2[x]*smooth_k[1];
+ float t1 = src3[x] - src[x];
+ buffer0[x] = t0; buffer1[x] = t1;
+ }
+
+ for( x = 0; x < dst_width; x++ )
+ {
+ float t0 = buffer0[x+2] - buffer0[x];
+ float t1 = (buffer1[x] + buffer1[x+2])*smooth_k[0] + buffer1[x+1]*smooth_k[1];
+ dstX[x] = t0; dstY[x] = t1;
+ }
+ }
+}
+
+
+CV_IMPL void
+cvCalcOpticalFlowPyrLK( const void* arrA, const void* arrB,
+ void* pyrarrA, void* pyrarrB,
+ const CvPoint2D32f * featuresA,
+ CvPoint2D32f * featuresB,
+ int count, CvSize winSize, int level,
+ char *status, float *error,
+ CvTermCriteria criteria, int flags )
+{
+ uchar *pyrBuffer = 0;
+ uchar *buffer = 0;
+ float* _error = 0;
+ char* _status = 0;
+
+ CV_FUNCNAME( "cvCalcOpticalFlowPyrLK" );
+
+ __BEGIN__;
+
+ const int MAX_ITERS = 100;
+
+ CvMat stubA, *imgA = (CvMat*)arrA;
+ CvMat stubB, *imgB = (CvMat*)arrB;
+ CvMat pstubA, *pyrA = (CvMat*)pyrarrA;
+ CvMat pstubB, *pyrB = (CvMat*)pyrarrB;
+ CvSize imgSize;
+ static const float smoothKernel[] = { 0.09375, 0.3125, 0.09375 }; /* 3/32, 10/32, 3/32 */
+
+ int bufferBytes = 0;
+ uchar **imgI = 0;
+ uchar **imgJ = 0;
+ int *step = 0;
+ double *scale = 0;
+ CvSize* size = 0;
+
+ int threadCount = cvGetNumThreads();
+ float* _patchI[CV_MAX_THREADS];
+ float* _patchJ[CV_MAX_THREADS];
+ float* _Ix[CV_MAX_THREADS];
+ float* _Iy[CV_MAX_THREADS];
+
+ int i, l;
+
+ CvSize patchSize = cvSize( winSize.width * 2 + 1, winSize.height * 2 + 1 );
+ int patchLen = patchSize.width * patchSize.height;
+ int srcPatchLen = (patchSize.width + 2)*(patchSize.height + 2);
+
+ CV_CALL( imgA = cvGetMat( imgA, &stubA ));
+ CV_CALL( imgB = cvGetMat( imgB, &stubB ));
+
+ if( CV_MAT_TYPE( imgA->type ) != CV_8UC1 )
+ CV_ERROR( CV_StsUnsupportedFormat, "" );
+
+ if( !CV_ARE_TYPES_EQ( imgA, imgB ))
+ CV_ERROR( CV_StsUnmatchedFormats, "" );
+
+ if( !CV_ARE_SIZES_EQ( imgA, imgB ))
+ CV_ERROR( CV_StsUnmatchedSizes, "" );
+
+ if( imgA->step != imgB->step )
+ CV_ERROR( CV_StsUnmatchedSizes, "imgA and imgB must have equal steps" );
+
+ imgSize = cvGetMatSize( imgA );
+
+ if( pyrA )
+ {
+ CV_CALL( pyrA = cvGetMat( pyrA, &pstubA ));
+
+ if( pyrA->step*pyrA->height < icvMinimalPyramidSize( imgSize ) )
+ CV_ERROR( CV_StsBadArg, "pyramid A has insufficient size" );
+ }
+ else
+ {
+ pyrA = &pstubA;
+ pyrA->data.ptr = 0;
+ }
+
+ if( pyrB )
+ {
+ CV_CALL( pyrB = cvGetMat( pyrB, &pstubB ));
+
+ if( pyrB->step*pyrB->height < icvMinimalPyramidSize( imgSize ) )
+ CV_ERROR( CV_StsBadArg, "pyramid B has insufficient size" );
+ }
+ else
+ {
+ pyrB = &pstubB;
+ pyrB->data.ptr = 0;
+ }
+
+ if( count == 0 )
+ EXIT;
+
+ if( !featuresA || !featuresB )
+ CV_ERROR( CV_StsNullPtr, "Some of arrays of point coordinates are missing" );
+
+ if( count < 0 )
+ CV_ERROR( CV_StsOutOfRange, "The number of tracked points is negative or zero" );
+
+ if( winSize.width <= 1 || winSize.height <= 1 )
+ CV_ERROR( CV_StsBadSize, "Invalid search window size" );
+
+ for( i = 0; i < threadCount; i++ )
+ _patchI[i] = _patchJ[i] = _Ix[i] = _Iy[i] = 0;
+
+ CV_CALL( icvInitPyramidalAlgorithm( imgA, imgB, pyrA, pyrB,
+ level, &criteria, MAX_ITERS, flags,
+ &imgI, &imgJ, &step, &size, &scale, &pyrBuffer ));
+
+ if( !status )
+ CV_CALL( status = _status = (char*)cvAlloc( count*sizeof(_status[0]) ));
+
+ /* buffer_size = <size for patches> + <size for pyramids> */
+ bufferBytes = (srcPatchLen + patchLen * 3) * sizeof( _patchI[0][0] ) * threadCount;
+ CV_CALL( buffer = (uchar*)cvAlloc( bufferBytes ));
+
+ for( i = 0; i < threadCount; i++ )
+ {
+ _patchI[i] = i == 0 ? (float*)buffer : _Iy[i-1] + patchLen;
+ _patchJ[i] = _patchI[i] + srcPatchLen;
+ _Ix[i] = _patchJ[i] + patchLen;
+ _Iy[i] = _Ix[i] + patchLen;
+ }
+
+ memset( status, 1, count );
+ if( error )
+ memset( error, 0, count*sizeof(error[0]) );
+
+ if( !(flags & CV_LKFLOW_INITIAL_GUESSES) )
+ memcpy( featuresB, featuresA, count*sizeof(featuresA[0]));
+
+ /* do processing from top pyramid level (smallest image)
+ to the bottom (original image) */
+ for( l = level; l >= 0; l-- )
+ {
+ CvSize levelSize = size[l];
+ int levelStep = step[l];
+
+ {
+#ifdef _OPENMP
+ #pragma omp parallel for num_threads(threadCount) schedule(dynamic)
+#endif // _OPENMP
+ /* find flow for each given point */
+ for( i = 0; i < count; i++ )
+ {
+ CvPoint2D32f v;
+ CvPoint minI, maxI, minJ, maxJ;
+ CvSize isz, jsz;
+ int pt_status;
+ CvPoint2D32f u;
+ CvPoint prev_minJ = { -1, -1 }, prev_maxJ = { -1, -1 };
+ double Gxx = 0, Gxy = 0, Gyy = 0, D = 0, minEig = 0;
+ float prev_mx = 0, prev_my = 0;
+ int j, x, y;
+ int threadIdx = cvGetThreadNum();
+ float* patchI = _patchI[threadIdx];
+ float* patchJ = _patchJ[threadIdx];
+ float* Ix = _Ix[threadIdx];
+ float* Iy = _Iy[threadIdx];
+
+ v.x = featuresB[i].x;
+ v.y = featuresB[i].y;
+ if( l < level )
+ {
+ v.x += v.x;
+ v.y += v.y;
+ }
+ else
+ {
+ v.x = (float)(v.x * scale[l]);
+ v.y = (float)(v.y * scale[l]);
+ }
+
+ pt_status = status[i];
+ if( !pt_status )
+ continue;
+
+ minI = maxI = minJ = maxJ = cvPoint( 0, 0 );
+
+ u.x = (float) (featuresA[i].x * scale[l]);
+ u.y = (float) (featuresA[i].y * scale[l]);
+
+ intersect( u, winSize, levelSize, &minI, &maxI );
+ isz = jsz = cvSize(maxI.x - minI.x + 2, maxI.y - minI.y + 2);
+ u.x += (minI.x - (patchSize.width - maxI.x + 1))*0.5f;
+ u.y += (minI.y - (patchSize.height - maxI.y + 1))*0.5f;
+
+ if( isz.width < 3 || isz.height < 3 ||
+ icvGetRectSubPix_8u32f_C1R( imgI[l], levelStep, levelSize,
+ patchI, isz.width*sizeof(patchI[0]), isz, u ) < 0 )
+ {
+ /* point is outside the image. take the next */
+ status[i] = 0;
+ continue;
+ }
+
+ icvCalcIxIy_32f( patchI, isz.width*sizeof(patchI[0]), Ix, Iy,
+ (isz.width-2)*sizeof(patchI[0]), isz, smoothKernel, patchJ );
+
+ for( j = 0; j < criteria.max_iter; j++ )
+ {
+ double bx = 0, by = 0;
+ float mx, my;
+ CvPoint2D32f _v;
+
+ intersect( v, winSize, levelSize, &minJ, &maxJ );
+
+ minJ.x = MAX( minJ.x, minI.x );
+ minJ.y = MAX( minJ.y, minI.y );
+
+ maxJ.x = MIN( maxJ.x, maxI.x );
+ maxJ.y = MIN( maxJ.y, maxI.y );
+
+ jsz = cvSize(maxJ.x - minJ.x, maxJ.y - minJ.y);
+
+ _v.x = v.x + (minJ.x - (patchSize.width - maxJ.x + 1))*0.5f;
+ _v.y = v.y + (minJ.y - (patchSize.height - maxJ.y + 1))*0.5f;
+
+ if( jsz.width < 1 || jsz.height < 1 ||
+ icvGetRectSubPix_8u32f_C1R( imgJ[l], levelStep, levelSize, patchJ,
+ jsz.width*sizeof(patchJ[0]), jsz, _v ) < 0 )
+ {
+ /* point is outside image. take the next */
+ pt_status = 0;
+ break;
+ }
+
+ if( maxJ.x == prev_maxJ.x && maxJ.y == prev_maxJ.y &&
+ minJ.x == prev_minJ.x && minJ.y == prev_minJ.y )
+ {
+ for( y = 0; y < jsz.height; y++ )
+ {
+ const float* pi = patchI +
+ (y + minJ.y - minI.y + 1)*isz.width + minJ.x - minI.x + 1;
+ const float* pj = patchJ + y*jsz.width;
+ const float* ix = Ix +
+ (y + minJ.y - minI.y)*(isz.width-2) + minJ.x - minI.x;
+ const float* iy = Iy + (ix - Ix);
+
+ for( x = 0; x < jsz.width; x++ )
+ {
+ double t0 = pi[x] - pj[x];
+ bx += t0 * ix[x];
+ by += t0 * iy[x];
+ }
+ }
+ }
+ else
+ {
+ Gxx = Gyy = Gxy = 0;
+ for( y = 0; y < jsz.height; y++ )
+ {
+ const float* pi = patchI +
+ (y + minJ.y - minI.y + 1)*isz.width + minJ.x - minI.x + 1;
+ const float* pj = patchJ + y*jsz.width;
+ const float* ix = Ix +
+ (y + minJ.y - minI.y)*(isz.width-2) + minJ.x - minI.x;
+ const float* iy = Iy + (ix - Ix);
+
+ for( x = 0; x < jsz.width; x++ )
+ {
+ double t = pi[x] - pj[x];
+ bx += (double) (t * ix[x]);
+ by += (double) (t * iy[x]);
+ Gxx += ix[x] * ix[x];
+ Gxy += ix[x] * iy[x];
+ Gyy += iy[x] * iy[x];
+ }
+ }
+
+ D = Gxx * Gyy - Gxy * Gxy;
+ if( D < DBL_EPSILON )
+ {
+ pt_status = 0;
+ break;
+ }
+
+ // Adi Shavit - 2008.05
+ if( flags & CV_LKFLOW_GET_MIN_EIGENVALS )
+ minEig = (Gyy + Gxx - sqrt((Gxx-Gyy)*(Gxx-Gyy) + 4.*Gxy*Gxy))/(2*jsz.height*jsz.width);
+
+ D = 1. / D;
+
+ prev_minJ = minJ;
+ prev_maxJ = maxJ;
+ }
+
+ mx = (float) ((Gyy * bx - Gxy * by) * D);
+ my = (float) ((Gxx * by - Gxy * bx) * D);
+
+ v.x += mx;
+ v.y += my;
+
+ if( mx * mx + my * my < criteria.epsilon )
+ break;
+
+ if( j > 0 && fabs(mx + prev_mx) < 0.01 && fabs(my + prev_my) < 0.01 )
+ {
+ v.x -= mx*0.5f;
+ v.y -= my*0.5f;
+ break;
+ }
+ prev_mx = mx;
+ prev_my = my;
+ }
+
+ featuresB[i] = v;
+ status[i] = (char)pt_status;
+ if( l == 0 && error && pt_status )
+ {
+ /* calc error */
+ double err = 0;
+ if( flags & CV_LKFLOW_GET_MIN_EIGENVALS )
+ err = minEig;
+ else
+ {
+ for( y = 0; y < jsz.height; y++ )
+ {
+ const float* pi = patchI +
+ (y + minJ.y - minI.y + 1)*isz.width + minJ.x - minI.x + 1;
+ const float* pj = patchJ + y*jsz.width;
+
+ for( x = 0; x < jsz.width; x++ )
+ {
+ double t = pi[x] - pj[x];
+ err += t * t;
+ }
+ }
+ err = sqrt(err);
+ }
+ error[i] = (float)err;
+ }
+ } // end of point processing loop (i)
+ }
+ } // end of pyramid levels loop (l)
+
+ __END__;
+
+ cvFree( &pyrBuffer );
+ cvFree( &buffer );
+ cvFree( &_error );
+ cvFree( &_status );
+}
+
+
+/* Affine tracking algorithm */
+
+CV_IMPL void
+cvCalcAffineFlowPyrLK( const void* arrA, const void* arrB,
+ void* pyrarrA, void* pyrarrB,
+ const CvPoint2D32f * featuresA,
+ CvPoint2D32f * featuresB,
+ float *matrices, int count,
+ CvSize winSize, int level,
+ char *status, float *error,
+ CvTermCriteria criteria, int flags )
+{
+ const int MAX_ITERS = 100;
+
+ char* _status = 0;
+ uchar *buffer = 0;
+ uchar *pyr_buffer = 0;
+
+ CV_FUNCNAME( "cvCalcAffineFlowPyrLK" );
+
+ __BEGIN__;
+
+ CvMat stubA, *imgA = (CvMat*)arrA;
+ CvMat stubB, *imgB = (CvMat*)arrB;
+ CvMat pstubA, *pyrA = (CvMat*)pyrarrA;
+ CvMat pstubB, *pyrB = (CvMat*)pyrarrB;
+
+ static const float smoothKernel[] = { 0.09375, 0.3125, 0.09375 }; /* 3/32, 10/32, 3/32 */
+
+ int bufferBytes = 0;
+
+ uchar **imgI = 0;
+ uchar **imgJ = 0;
+ int *step = 0;
+ double *scale = 0;
+ CvSize* size = 0;
+
+ float *patchI;
+ float *patchJ;
+ float *Ix;
+ float *Iy;
+
+ int i, j, k, l;
+
+ CvSize patchSize = cvSize( winSize.width * 2 + 1, winSize.height * 2 + 1 );
+ int patchLen = patchSize.width * patchSize.height;
+ int patchStep = patchSize.width * sizeof( patchI[0] );
+
+ CvSize srcPatchSize = cvSize( patchSize.width + 2, patchSize.height + 2 );
+ int srcPatchLen = srcPatchSize.width * srcPatchSize.height;
+ int srcPatchStep = srcPatchSize.width * sizeof( patchI[0] );
+ CvSize imgSize;
+ float eps = (float)MIN(winSize.width, winSize.height);
+
+ CV_CALL( imgA = cvGetMat( imgA, &stubA ));
+ CV_CALL( imgB = cvGetMat( imgB, &stubB ));
+
+ if( CV_MAT_TYPE( imgA->type ) != CV_8UC1 )
+ CV_ERROR( CV_StsUnsupportedFormat, "" );
+
+ if( !CV_ARE_TYPES_EQ( imgA, imgB ))
+ CV_ERROR( CV_StsUnmatchedFormats, "" );
+
+ if( !CV_ARE_SIZES_EQ( imgA, imgB ))
+ CV_ERROR( CV_StsUnmatchedSizes, "" );
+
+ if( imgA->step != imgB->step )
+ CV_ERROR( CV_StsUnmatchedSizes, "imgA and imgB must have equal steps" );
+
+ if( !matrices )
+ CV_ERROR( CV_StsNullPtr, "" );
+
+ imgSize = cvGetMatSize( imgA );
+
+ if( pyrA )
+ {
+ CV_CALL( pyrA = cvGetMat( pyrA, &pstubA ));
+
+ if( pyrA->step*pyrA->height < icvMinimalPyramidSize( imgSize ) )
+ CV_ERROR( CV_StsBadArg, "pyramid A has insufficient size" );
+ }
+ else
+ {
+ pyrA = &pstubA;
+ pyrA->data.ptr = 0;
+ }
+
+ if( pyrB )
+ {
+ CV_CALL( pyrB = cvGetMat( pyrB, &pstubB ));
+
+ if( pyrB->step*pyrB->height < icvMinimalPyramidSize( imgSize ) )
+ CV_ERROR( CV_StsBadArg, "pyramid B has insufficient size" );
+ }
+ else
+ {
+ pyrB = &pstubB;
+ pyrB->data.ptr = 0;
+ }
+
+ if( count == 0 )
+ EXIT;
+
+ /* check input arguments */
+ if( !featuresA || !featuresB || !matrices )
+ CV_ERROR( CV_StsNullPtr, "" );
+
+ if( winSize.width <= 1 || winSize.height <= 1 )
+ CV_ERROR( CV_StsOutOfRange, "the search window is too small" );
+
+ if( count < 0 )
+ CV_ERROR( CV_StsOutOfRange, "" );
+
+ CV_CALL( icvInitPyramidalAlgorithm( imgA, imgB,
+ pyrA, pyrB, level, &criteria, MAX_ITERS, flags,
+ &imgI, &imgJ, &step, &size, &scale, &pyr_buffer ));
+
+ /* buffer_size = <size for patches> + <size for pyramids> */
+ bufferBytes = (srcPatchLen + patchLen*3)*sizeof(patchI[0]) + (36*2 + 6)*sizeof(double);
+
+ CV_CALL( buffer = (uchar*)cvAlloc(bufferBytes));
+
+ if( !status )
+ CV_CALL( status = _status = (char*)cvAlloc(count) );
+
+ patchI = (float *) buffer;
+ patchJ = patchI + srcPatchLen;
+ Ix = patchJ + patchLen;
+ Iy = Ix + patchLen;
+
+ if( status )
+ memset( status, 1, count );
+
+ if( !(flags & CV_LKFLOW_INITIAL_GUESSES) )
+ {
+ memcpy( featuresB, featuresA, count * sizeof( featuresA[0] ));
+ for( i = 0; i < count * 4; i += 4 )
+ {
+ matrices[i] = matrices[i + 3] = 1.f;
+ matrices[i + 1] = matrices[i + 2] = 0.f;
+ }
+ }
+
+ for( i = 0; i < count; i++ )
+ {
+ featuresB[i].x = (float)(featuresB[i].x * scale[level] * 0.5);
+ featuresB[i].y = (float)(featuresB[i].y * scale[level] * 0.5);
+ }
+
+ /* do processing from top pyramid level (smallest image)
+ to the bottom (original image) */
+ for( l = level; l >= 0; l-- )
+ {
+ CvSize levelSize = size[l];
+ int levelStep = step[l];
+
+ /* find flow for each given point at the particular level */
+ for( i = 0; i < count; i++ )
+ {
+ CvPoint2D32f u;
+ float Av[6];
+ double G[36];
+ double meanI = 0, meanJ = 0;
+ int x, y;
+ int pt_status = status[i];
+ CvMat mat;
+
+ if( !pt_status )
+ continue;
+
+ Av[0] = matrices[i*4];
+ Av[1] = matrices[i*4+1];
+ Av[3] = matrices[i*4+2];
+ Av[4] = matrices[i*4+3];
+
+ Av[2] = featuresB[i].x += featuresB[i].x;
+ Av[5] = featuresB[i].y += featuresB[i].y;
+
+ u.x = (float) (featuresA[i].x * scale[l]);
+ u.y = (float) (featuresA[i].y * scale[l]);
+
+ if( u.x < -eps || u.x >= levelSize.width+eps ||
+ u.y < -eps || u.y >= levelSize.height+eps ||
+ icvGetRectSubPix_8u32f_C1R( imgI[l], levelStep,
+ levelSize, patchI, srcPatchStep, srcPatchSize, u ) < 0 )
+ {
+ /* point is outside the image. take the next */
+ if( l == 0 )
+ status[i] = 0;
+ continue;
+ }
+
+ icvCalcIxIy_32f( patchI, srcPatchStep, Ix, Iy,
+ (srcPatchSize.width-2)*sizeof(patchI[0]), srcPatchSize,
+ smoothKernel, patchJ );
+
+ /* repack patchI (remove borders) */
+ for( k = 0; k < patchSize.height; k++ )
+ memcpy( patchI + k * patchSize.width,
+ patchI + (k + 1) * srcPatchSize.width + 1, patchStep );
+
+ memset( G, 0, sizeof( G ));
+
+ /* calculate G matrix */
+ for( y = -winSize.height, k = 0; y <= winSize.height; y++ )
+ {
+ for( x = -winSize.width; x <= winSize.width; x++, k++ )
+ {
+ double ixix = ((double) Ix[k]) * Ix[k];
+ double ixiy = ((double) Ix[k]) * Iy[k];
+ double iyiy = ((double) Iy[k]) * Iy[k];
+
+ double xx, xy, yy;
+
+ G[0] += ixix;
+ G[1] += ixiy;
+ G[2] += x * ixix;
+ G[3] += y * ixix;
+ G[4] += x * ixiy;
+ G[5] += y * ixiy;
+
+ // G[6] == G[1]
+ G[7] += iyiy;
+ // G[8] == G[4]
+ // G[9] == G[5]
+ G[10] += x * iyiy;
+ G[11] += y * iyiy;
+
+ xx = x * x;
+ xy = x * y;
+ yy = y * y;
+
+ // G[12] == G[2]
+ // G[13] == G[8] == G[4]
+ G[14] += xx * ixix;
+ G[15] += xy * ixix;
+ G[16] += xx * ixiy;
+ G[17] += xy * ixiy;
+
+ // G[18] == G[3]
+ // G[19] == G[9]
+ // G[20] == G[15]
+ G[21] += yy * ixix;
+ // G[22] == G[17]
+ G[23] += yy * ixiy;
+
+ // G[24] == G[4]
+ // G[25] == G[10]
+ // G[26] == G[16]
+ // G[27] == G[22]
+ G[28] += xx * iyiy;
+ G[29] += xy * iyiy;
+
+ // G[30] == G[5]
+ // G[31] == G[11]
+ // G[32] == G[17]
+ // G[33] == G[23]
+ // G[34] == G[29]
+ G[35] += yy * iyiy;
+
+ meanI += patchI[k];
+ }
+ }
+
+ meanI /= patchSize.width*patchSize.height;
+
+ G[8] = G[4];
+ G[9] = G[5];
+ G[22] = G[17];
+
+ // fill part of G below its diagonal
+ for( y = 1; y < 6; y++ )
+ for( x = 0; x < y; x++ )
+ G[y * 6 + x] = G[x * 6 + y];
+
+ cvInitMatHeader( &mat, 6, 6, CV_64FC1, G );
+
+ if( cvInvert( &mat, &mat, CV_SVD ) < 1e-4 )
+ {
+ /* bad matrix. take the next point */
+ if( l == 0 )
+ status[i] = 0;
+ continue;
+ }
+
+ for( j = 0; j < criteria.max_iter; j++ )
+ {
+ double b[6] = {0,0,0,0,0,0}, eta[6];
+ double t0, t1, s = 0;
+
+ if( Av[2] < -eps || Av[2] >= levelSize.width+eps ||
+ Av[5] < -eps || Av[5] >= levelSize.height+eps ||
+ icvGetQuadrangleSubPix_8u32f_C1R( imgJ[l], levelStep,
+ levelSize, patchJ, patchStep, patchSize, Av ) < 0 )
+ {
+ pt_status = 0;
+ break;
+ }
+
+ for( y = -winSize.height, k = 0, meanJ = 0; y <= winSize.height; y++ )
+ for( x = -winSize.width; x <= winSize.width; x++, k++ )
+ meanJ += patchJ[k];
+
+ meanJ = meanJ / (patchSize.width * patchSize.height) - meanI;
+
+ for( y = -winSize.height, k = 0; y <= winSize.height; y++ )
+ {
+ for( x = -winSize.width; x <= winSize.width; x++, k++ )
+ {
+ double t = patchI[k] - patchJ[k] + meanJ;
+ double ixt = Ix[k] * t;
+ double iyt = Iy[k] * t;
+
+ s += t;
+
+ b[0] += ixt;
+ b[1] += iyt;
+ b[2] += x * ixt;
+ b[3] += y * ixt;
+ b[4] += x * iyt;
+ b[5] += y * iyt;
+ }
+ }
+
+ icvTransformVector_64d( G, b, eta, 6, 6 );
+
+ Av[2] = (float)(Av[2] + Av[0] * eta[0] + Av[1] * eta[1]);
+ Av[5] = (float)(Av[5] + Av[3] * eta[0] + Av[4] * eta[1]);
+
+ t0 = Av[0] * (1 + eta[2]) + Av[1] * eta[4];
+ t1 = Av[0] * eta[3] + Av[1] * (1 + eta[5]);
+ Av[0] = (float)t0;
+ Av[1] = (float)t1;
+
+ t0 = Av[3] * (1 + eta[2]) + Av[4] * eta[4];
+ t1 = Av[3] * eta[3] + Av[4] * (1 + eta[5]);
+ Av[3] = (float)t0;
+ Av[4] = (float)t1;
+
+ if( eta[0] * eta[0] + eta[1] * eta[1] < criteria.epsilon )
+ break;
+ }
+
+ if( pt_status != 0 || l == 0 )
+ {
+ status[i] = (char)pt_status;
+ featuresB[i].x = Av[2];
+ featuresB[i].y = Av[5];
+
+ matrices[i*4] = Av[0];
+ matrices[i*4+1] = Av[1];
+ matrices[i*4+2] = Av[3];
+ matrices[i*4+3] = Av[4];
+ }
+
+ if( pt_status && l == 0 && error )
+ {
+ /* calc error */
+ double err = 0;
+
+ for( y = 0, k = 0; y < patchSize.height; y++ )
+ {
+ for( x = 0; x < patchSize.width; x++, k++ )
+ {
+ double t = patchI[k] - patchJ[k] + meanJ;
+ err += t * t;
+ }
+ }
+ error[i] = (float)sqrt(err);
+ }
+ }
+ }
+
+ __END__;
+
+ cvFree( &pyr_buffer );
+ cvFree( &buffer );
+ cvFree( &_status );
+}
+
+
+
+static void
+icvGetRTMatrix( const CvPoint2D32f* a, const CvPoint2D32f* b,
+ int count, CvMat* M, int full_affine )
+{
+ if( full_affine )
+ {
+ double sa[36], sb[6];
+ CvMat A = cvMat( 6, 6, CV_64F, sa ), B = cvMat( 6, 1, CV_64F, sb );
+ CvMat MM = cvMat( 6, 1, CV_64F, M->data.db );
+
+ int i;
+
+ memset( sa, 0, sizeof(sa) );
+ memset( sb, 0, sizeof(sb) );
+
+ for( i = 0; i < count; i++ )
+ {
+ sa[0] += a[i].x*a[i].x;
+ sa[1] += a[i].y*a[i].x;
+ sa[2] += a[i].x;
+
+ sa[6] += a[i].x*a[i].y;
+ sa[7] += a[i].y*a[i].y;
+ sa[8] += a[i].y;
+
+ sa[12] += a[i].x;
+ sa[13] += a[i].y;
+ sa[14] += 1;
+
+ sb[0] += a[i].x*b[i].x;
+ sb[1] += a[i].y*b[i].x;
+ sb[2] += b[i].x;
+ sb[3] += a[i].x*b[i].y;
+ sb[4] += a[i].y*b[i].y;
+ sb[5] += b[i].y;
+ }
+
+ sa[21] = sa[0];
+ sa[22] = sa[1];
+ sa[23] = sa[2];
+ sa[27] = sa[6];
+ sa[28] = sa[7];
+ sa[29] = sa[8];
+ sa[33] = sa[12];
+ sa[34] = sa[13];
+ sa[35] = sa[14];
+
+ cvSolve( &A, &B, &MM, CV_SVD );
+ }
+ else
+ {
+ double sa[16], sb[4], m[4], *om = M->data.db;
+ CvMat A = cvMat( 4, 4, CV_64F, sa ), B = cvMat( 4, 1, CV_64F, sb );
+ CvMat MM = cvMat( 4, 1, CV_64F, m );
+
+ int i;
+
+ memset( sa, 0, sizeof(sa) );
+ memset( sb, 0, sizeof(sb) );
+
+ for( i = 0; i < count; i++ )
+ {
+ sa[0] += a[i].x*a[i].x + a[i].y*a[i].y;
+ sa[1] += 0;
+ sa[2] += a[i].x;
+ sa[3] += a[i].y;
+
+ sa[4] += 0;
+ sa[5] += a[i].x*a[i].x + a[i].y*a[i].y;
+ sa[6] += -a[i].y;
+ sa[7] += a[i].x;
+
+ sa[8] += a[i].x;
+ sa[9] += -a[i].y;
+ sa[10] += 1;
+ sa[11] += 0;
+
+ sa[12] += a[i].y;
+ sa[13] += a[i].x;
+ sa[14] += 0;
+ sa[15] += 1;
+
+ sb[0] += a[i].x*b[i].x + a[i].y*b[i].y;
+ sb[1] += a[i].x*b[i].y - a[i].y*b[i].x;
+ sb[2] += b[i].x;
+ sb[3] += b[i].y;
+ }
+
+ cvSolve( &A, &B, &MM, CV_SVD );
+
+ om[0] = om[4] = m[0];
+ om[1] = -m[1];
+ om[3] = m[1];
+ om[2] = m[2];
+ om[5] = m[3];
+ }
+}
+
+
+CV_IMPL int
+cvEstimateRigidTransform( const CvArr* _A, const CvArr* _B, CvMat* _M, int full_affine )
+{
+ int result = 0;
+
+ const int COUNT = 15;
+ const int WIDTH = 160, HEIGHT = 120;
+ const int RANSAC_MAX_ITERS = 100;
+ const int RANSAC_SIZE0 = 3;
+ const double MIN_TRIANGLE_SIDE = 20;
+ const double RANSAC_GOOD_RATIO = 0.5;
+
+ int allocated = 1;
+ CvMat *sA = 0, *sB = 0;
+ CvPoint2D32f *pA = 0, *pB = 0;
+ int* good_idx = 0;
+ char *status = 0;
+ CvMat* gray = 0;
+
+ CV_FUNCNAME( "cvEstimateRigidTransform" );
+
+ __BEGIN__;
+
+ CvMat stubA, *A;
+ CvMat stubB, *B;
+ CvSize sz0, sz1;
+ int cn, equal_sizes;
+ int i, j, k, k1;
+ int count_x, count_y, count;
+ double scale = 1;
+ CvRNG rng = cvRNG(-1);
+ double m[6]={0};
+ CvMat M = cvMat( 2, 3, CV_64F, m );
+ int good_count = 0;
+
+ CV_CALL( A = cvGetMat( _A, &stubA ));
+ CV_CALL( B = cvGetMat( _B, &stubB ));
+
+ if( !CV_IS_MAT(_M) )
+ CV_ERROR( _M ? CV_StsBadArg : CV_StsNullPtr, "Output parameter M is not a valid matrix" );
+
+ if( !CV_ARE_SIZES_EQ( A, B ) )
+ CV_ERROR( CV_StsUnmatchedSizes, "Both input images must have the same size" );
+
+ if( !CV_ARE_TYPES_EQ( A, B ) )
+ CV_ERROR( CV_StsUnmatchedFormats, "Both input images must have the same data type" );
+
+ if( CV_MAT_TYPE(A->type) == CV_8UC1 || CV_MAT_TYPE(A->type) == CV_8UC3 )
+ {
+ cn = CV_MAT_CN(A->type);
+ sz0 = cvGetSize(A);
+ sz1 = cvSize(WIDTH, HEIGHT);
+
+ scale = MAX( (double)sz1.width/sz0.width, (double)sz1.height/sz0.height );
+ scale = MIN( scale, 1. );
+ sz1.width = cvRound( sz0.width * scale );
+ sz1.height = cvRound( sz0.height * scale );
+
+ equal_sizes = sz1.width == sz0.width && sz1.height == sz0.height;
+
+ if( !equal_sizes || cn != 1 )
+ {
+ CV_CALL( sA = cvCreateMat( sz1.height, sz1.width, CV_8UC1 ));
+ CV_CALL( sB = cvCreateMat( sz1.height, sz1.width, CV_8UC1 ));
+
+ if( !equal_sizes && cn != 1 )
+ CV_CALL( gray = cvCreateMat( sz0.height, sz0.width, CV_8UC1 ));
+
+ if( gray )
+ {
+ cvCvtColor( A, gray, CV_BGR2GRAY );
+ cvResize( gray, sA, CV_INTER_AREA );
+ cvCvtColor( B, gray, CV_BGR2GRAY );
+ cvResize( gray, sB, CV_INTER_AREA );
+ }
+ else if( cn == 1 )
+ {
+ cvResize( gray, sA, CV_INTER_AREA );
+ cvResize( gray, sB, CV_INTER_AREA );
+ }
+ else
+ {
+ cvCvtColor( A, gray, CV_BGR2GRAY );
+ cvResize( gray, sA, CV_INTER_AREA );
+ cvCvtColor( B, gray, CV_BGR2GRAY );
+ }
+
+ cvReleaseMat( &gray );
+ A = sA;
+ B = sB;
+ }
+
+ count_y = COUNT;
+ count_x = cvRound((double)COUNT*sz1.width/sz1.height);
+ count = count_x * count_y;
+
+ CV_CALL( pA = (CvPoint2D32f*)cvAlloc( count*sizeof(pA[0]) ));
+ CV_CALL( pB = (CvPoint2D32f*)cvAlloc( count*sizeof(pB[0]) ));
+ CV_CALL( status = (char*)cvAlloc( count*sizeof(status[0]) ));
+
+ for( i = 0, k = 0; i < count_y; i++ )
+ for( j = 0; j < count_x; j++, k++ )
+ {
+ pA[k].x = (j+0.5f)*sz1.width/count_x;
+ pA[k].y = (i+0.5f)*sz1.height/count_y;
+ }
+
+ // find the corresponding points in B
+ cvCalcOpticalFlowPyrLK( A, B, 0, 0, pA, pB, count, cvSize(10,10), 3,
+ status, 0, cvTermCriteria(CV_TERMCRIT_ITER,40,0.1), 0 );
+
+ // repack the remained points
+ for( i = 0, k = 0; i < count; i++ )
+ if( status[i] )
+ {
+ if( i > k )
+ {
+ pA[k] = pA[i];
+ pB[k] = pB[i];
+ }
+ k++;
+ }
+
+ count = k;
+ }
+ else if( CV_MAT_TYPE(A->type) == CV_32FC2 || CV_MAT_TYPE(A->type) == CV_32SC2 )
+ {
+ count = A->cols*A->rows;
+
+ if( CV_IS_MAT_CONT(A->type & B->type) && CV_MAT_TYPE(A->type) == CV_32FC2 )
+ {
+ pA = (CvPoint2D32f*)A->data.ptr;
+ pB = (CvPoint2D32f*)B->data.ptr;
+ allocated = 0;
+ }
+ else
+ {
+ CvMat _pA, _pB;
+
+ CV_CALL( pA = (CvPoint2D32f*)cvAlloc( count*sizeof(pA[0]) ));
+ CV_CALL( pB = (CvPoint2D32f*)cvAlloc( count*sizeof(pB[0]) ));
+ _pA = cvMat( A->rows, A->cols, CV_32FC2, pA );
+ _pB = cvMat( B->rows, B->cols, CV_32FC2, pB );
+ cvConvert( A, &_pA );
+ cvConvert( B, &_pB );
+ }
+ }
+ else
+ CV_ERROR( CV_StsUnsupportedFormat, "Both input images must have either 8uC1 or 8uC3 type" );
+
+ CV_CALL( good_idx = (int*)cvAlloc( count*sizeof(good_idx[0]) ));
+
+ if( count < RANSAC_SIZE0 )
+ EXIT;
+
+ // RANSAC stuff:
+ // 1. find the consensus
+ for( k = 0; k < RANSAC_MAX_ITERS; k++ )
+ {
+ int idx[RANSAC_SIZE0];
+ CvPoint2D32f a[3];
+ CvPoint2D32f b[3];
+
+ memset( a, 0, sizeof(a) );
+ memset( b, 0, sizeof(b) );
+
+ // choose random 3 non-complanar points from A & B
+ for( i = 0; i < RANSAC_SIZE0; i++ )
+ {
+ for( k1 = 0; k1 < RANSAC_MAX_ITERS; k1++ )
+ {
+ idx[i] = cvRandInt(&rng) % count;
+
+ for( j = 0; j < i; j++ )
+ {
+ if( idx[j] == idx[i] )
+ break;
+ // check that the points are not very close one each other
+ if( fabs(pA[idx[i]].x - pA[idx[j]].x) +
+ fabs(pA[idx[i]].y - pA[idx[j]].y) < MIN_TRIANGLE_SIDE )
+ break;
+ if( fabs(pB[idx[i]].x - pB[idx[j]].x) +
+ fabs(pB[idx[i]].y - pB[idx[j]].y) < MIN_TRIANGLE_SIDE )
+ break;
+ }
+
+ if( j < i )
+ continue;
+
+ if( i+1 == RANSAC_SIZE0 )
+ {
+ // additional check for non-complanar vectors
+ a[0] = pA[idx[0]];
+ a[1] = pA[idx[1]];
+ a[2] = pA[idx[2]];
+
+ b[0] = pB[idx[0]];
+ b[1] = pB[idx[1]];
+ b[2] = pB[idx[2]];
+
+ if( fabs((a[1].x - a[0].x)*(a[2].y - a[0].y) - (a[1].y - a[0].y)*(a[2].x - a[0].x)) < 1 ||
+ fabs((b[1].x - b[0].x)*(b[2].y - b[0].y) - (b[1].y - b[0].y)*(b[2].x - b[0].x)) < 1 )
+ continue;
+ }
+ break;
+ }
+
+ if( k1 >= RANSAC_MAX_ITERS )
+ break;
+ }
+
+ if( i < RANSAC_SIZE0 )
+ continue;
+
+ // estimate the transformation using 3 points
+ icvGetRTMatrix( a, b, 3, &M, full_affine );
+
+ for( i = 0, good_count = 0; i < count; i++ )
+ {
+ if( fabs( m[0]*pA[i].x + m[1]*pA[i].y + m[2] - pB[i].x ) +
+ fabs( m[3]*pA[i].x + m[4]*pA[i].y + m[5] - pB[i].y ) < 8 )
+ good_idx[good_count++] = i;
+ }
+
+ if( good_count >= count*RANSAC_GOOD_RATIO )
+ break;
+ }
+
+ if( k >= RANSAC_MAX_ITERS )
+ EXIT;
+
+ if( good_count < count )
+ {
+ for( i = 0; i < good_count; i++ )
+ {
+ j = good_idx[i];
+ pA[i] = pA[j];
+ pB[i] = pB[j];
+ }
+ }
+
+ icvGetRTMatrix( pA, pB, good_count, &M, full_affine );
+ m[2] /= scale;
+ m[5] /= scale;
+ CV_CALL( cvConvert( &M, _M ));
+ result = 1;
+
+ __END__;
+
+ cvReleaseMat( &sA );
+ cvReleaseMat( &sB );
+ cvFree( &pA );
+ cvFree( &pB );
+ cvFree( &status );
+ cvFree( &good_idx );
+ cvReleaseMat( &gray );
+
+ return result;
+}
+
+namespace cv
+{
+Mat estimateRigidTransform( const vector<Point2f>& A,
+ const vector<Point2f>& B,
+ bool fullAffine )
+{
+ Mat M(2, 3, CV_64F);
+ CvMat _A = Mat_<Point2f>(A), _B = Mat_<Point2f>(B), _M = M;
+ cvEstimateRigidTransform(&_A, &_B, &_M, fullAffine);
+ return M;
+}
+}
+
+/* End of file. */
projects / opencv / blobdiff