#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 )
int max_iters, int flags,
uchar *** imgI, uchar *** imgJ,
int **step, CvSize** size,
- double **scale, uchar ** buffer )
+ double **scale, cv::AutoBuffer<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( ((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" );
+ CV_Error( CV_StsOutOfRange, "The number of pyramid levels is negative" );
switch( criteria->type )
{
break;
default:
assert( 0 );
- CV_ERROR( CV_StsBadArg, "Invalid termination criteria" );
+ CV_Error( CV_StsBadArg, "Invalid termination criteria" );
}
/* compare squared values */
(sizeof(imgI[0][0]) * 2 + sizeof(step[0][0]) +
sizeof(size[0][0]) + sizeof(scale[0][0])) * level1);
- CV_CALL( *buffer = (uchar *)cvAlloc( bufferBytes ));
+ buffer->allocate( bufferBytes );
- *imgI = (uchar **) buffer[0];
+ *imgI = (uchar **) (uchar*)(*buffer);
*imgJ = *imgI + level1;
*step = (int *) (*imgJ + level1);
*scale = (double *) (*step + level1);
}
}
}
-
- __END__;
}
}
-icvOpticalFlowPyrLKInitAlloc_8u_C1R_t icvOpticalFlowPyrLKInitAlloc_8u_C1R_p = 0;
-icvOpticalFlowPyrLKFree_8u_C1R_t icvOpticalFlowPyrLKFree_8u_C1R_p = 0;
-icvOpticalFlowPyrLK_8u_C1R_t icvOpticalFlowPyrLK_8u_C1R_p = 0;
-
-
-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 )
+namespace cv
{
- uchar *pyrBuffer = 0;
- uchar *buffer = 0;
- float* _error = 0;
- char* _status = 0;
-
- void* ipp_optflow_state = 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]) ));
-
-#if 0
- if( icvOpticalFlowPyrLKInitAlloc_8u_C1R_p &&
- icvOpticalFlowPyrLKFree_8u_C1R_p &&
- icvOpticalFlowPyrLK_8u_C1R_p &&
- winSize.width == winSize.height &&
- icvOpticalFlowPyrLKInitAlloc_8u_C1R_p( &ipp_optflow_state, imgSize,
- winSize.width*2+1, cvAlgHintAccurate ) >= 0 )
- {
- CvPyramid ipp_pyrA, ipp_pyrB;
- static const double rate[] = { 1, 0.5, 0.25, 0.125, 0.0625, 0.03125, 0.015625, 0.0078125,
- 0.00390625, 0.001953125, 0.0009765625, 0.00048828125, 0.000244140625,
- 0.0001220703125 };
- // initialize pyramid structures
- assert( level < 14 );
- ipp_pyrA.ptr = imgI;
- ipp_pyrB.ptr = imgJ;
- ipp_pyrA.sz = ipp_pyrB.sz = size;
- ipp_pyrA.rate = ipp_pyrB.rate = (double*)rate;
- ipp_pyrA.step = ipp_pyrB.step = step;
- ipp_pyrA.state = ipp_pyrB.state = 0;
- ipp_pyrA.level = ipp_pyrB.level = level;
-
- if( !error )
- CV_CALL( error = _error = (float*)cvAlloc( count*sizeof(_error[0]) ));
-
- for( i = 0; i < count; i++ )
- featuresB[i] = featuresA[i];
-
- if( icvOpticalFlowPyrLK_8u_C1R_p( &ipp_pyrA, &ipp_pyrB,
- (const float*)featuresA, (float*)featuresB, status, error, count,
- winSize.width*2 + 1, level, criteria.max_iter,
- (float)criteria.epsilon, ipp_optflow_state ) >= 0 )
- {
- for( i = 0; i < count; i++ )
- status[i] = status[i] == 0;
- EXIT;
- }
- }
-#endif
- /* 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++ )
+struct LKTrackerInvoker
+{
+ LKTrackerInvoker( const CvMat* _imgI, const CvMat* _imgJ,
+ const CvPoint2D32f* _featuresA,
+ CvPoint2D32f* _featuresB,
+ char* _status, float* _error,
+ CvTermCriteria _criteria,
+ CvSize _winSize, int _level, int _flags )
{
- _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;
+ imgI = _imgI;
+ imgJ = _imgJ;
+ featuresA = _featuresA;
+ featuresB = _featuresB;
+ status = _status;
+ error = _error;
+ criteria = _criteria;
+ winSize = _winSize;
+ level = _level;
+ flags = _flags;
}
-
- 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-- )
+
+ void operator()(const BlockedRange& range) const
{
- 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++ )
+ static const float smoothKernel[] = { 0.09375, 0.3125, 0.09375 }; // 3/32, 10/32, 3/32
+
+ int i, i1 = range.begin(), i2 = range.end();
+
+ 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);
+
+ AutoBuffer<float> buf(patchLen*3 + srcPatchLen);
+ float* patchI = buf;
+ float* patchJ = patchI + srcPatchLen;
+ float* Ix = patchJ + patchLen;
+ float* Iy = Ix + patchLen;
+ float scaleL = 1.f/(1 << level);
+ CvSize levelSize = cvGetMatSize(imgI);
+
+ // find flow for each given point
+ for( i = i1; i < i2; i++ )
{
CvPoint2D32f v;
CvPoint minI, maxI, minJ, maxJ;
int pt_status;
CvPoint2D32f u;
CvPoint prev_minJ = { -1, -1 }, prev_maxJ = { -1, -1 };
- double Gxx = 0, Gxy = 0, Gyy = 0, D = 0;
+ 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]);
- }
-
+
+ v.x = featuresB[i].x*2;
+ v.y = featuresB[i].y*2;
+
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]);
-
+
+ minI = maxI = minJ = maxJ = cvPoint(0, 0);
+
+ u.x = featuresA[i].x * scaleL;
+ u.y = featuresA[i].y * scaleL;
+
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 )
+ icvGetRectSubPix_8u32f_C1R( imgI->data.ptr, imgI->step, levelSize,
+ patchI, isz.width*sizeof(patchI[0]), isz, u ) < 0 )
{
- /* point is outside the image. take the next */
+ // point is outside the first 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 );
-
+ (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,
+ icvGetRectSubPix_8u32f_C1R( imgJ->data.ptr, imgJ->step, levelSize, patchJ,
jsz.width*sizeof(patchJ[0]), jsz, _v ) < 0 )
{
- /* point is outside image. take the next */
+ // point is outside of the second 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;
+ (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;
+ (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];
for( y = 0; y < jsz.height; y++ )
{
const float* pi = patchI +
- (y + minJ.y - minI.y + 1)*isz.width + minJ.x - minI.x + 1;
+ (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;
+ (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];
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;
prev_mx = mx;
prev_my = my;
}
-
+
featuresB[i] = v;
status[i] = (char)pt_status;
- if( l == 0 && error && pt_status )
+ if( level == 0 && error && pt_status )
{
- /* calc error */
+ // calc error
double err = 0;
-
- for( y = 0; y < jsz.height; y++ )
+ if( flags & CV_LKFLOW_GET_MIN_EIGENVALS )
+ err = minEig;
+ else
{
- 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++ )
+ for( y = 0; y < jsz.height; y++ )
{
- double t = pi[x] - pj[x];
- err += t * t;
+ 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)sqrt(err);
+ error[i] = (float)err;
}
} // end of point processing loop (i)
- }
- } // end of pyramid levels loop (l)
+ }
+
+ const CvMat* imgI;
+ const CvMat* imgJ;
+ const CvPoint2D32f* featuresA;
+ CvPoint2D32f* featuresB;
+ char* status;
+ float* error;
+ CvTermCriteria criteria;
+ CvSize winSize;
+ int level;
+ int flags;
+};
+
+
+}
- __END__;
- if( ipp_optflow_state )
- icvOpticalFlowPyrLKFree_8u_C1R_p( ipp_optflow_state );
+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 )
+{
+ cv::AutoBuffer<uchar> pyrBuffer;
+ cv::AutoBuffer<uchar> buffer;
+ cv::AutoBuffer<char> _status;
+
+ const int MAX_ITERS = 100;
- cvFree( &pyrBuffer );
- cvFree( &buffer );
- cvFree( &_error );
- cvFree( &_status );
+ CvMat stubA, *imgA = (CvMat*)arrA;
+ CvMat stubB, *imgB = (CvMat*)arrB;
+ CvMat pstubA, *pyrA = (CvMat*)pyrarrA;
+ CvMat pstubB, *pyrB = (CvMat*)pyrarrB;
+ CvSize imgSize;
+
+ uchar **imgI = 0;
+ uchar **imgJ = 0;
+ int *step = 0;
+ double *scale = 0;
+ CvSize* size = 0;
+
+ int i, l;
+
+ imgA = cvGetMat( imgA, &stubA );
+ 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 )
+ {
+ 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 )
+ {
+ 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 )
+ return;
+
+ 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" );
+
+ icvInitPyramidalAlgorithm( imgA, imgB, pyrA, pyrB,
+ level, &criteria, MAX_ITERS, flags,
+ &imgI, &imgJ, &step, &size, &scale, &pyrBuffer );
+
+ if( !status )
+ {
+ _status.allocate(count);
+ status = _status;
+ }
+
+ 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]));
+
+ 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-- )
+ {
+ CvMat imgI_l, imgJ_l;
+ cvInitMatHeader(&imgI_l, size[l].height, size[l].width, imgA->type, imgI[l], step[l]);
+ cvInitMatHeader(&imgJ_l, size[l].height, size[l].width, imgB->type, imgJ[l], step[l]);
+
+ cv::parallel_for(cv::BlockedRange(0, count),
+ cv::LKTrackerInvoker(&imgI_l, &imgJ_l, featuresA,
+ featuresB, status, error,
+ criteria, winSize, l, flags));
+ } // end of pyramid levels loop (l)
}
{
const int MAX_ITERS = 100;
- char* _status = 0;
- uchar *buffer = 0;
- uchar *pyr_buffer = 0;
-
- CV_FUNCNAME( "cvCalcAffineFlowPyrLK" );
-
- __BEGIN__;
+ cv::AutoBuffer<char> _status;
+ cv::AutoBuffer<uchar> buffer;
+ cv::AutoBuffer<uchar> pyr_buffer;
CvMat stubA, *imgA = (CvMat*)arrA;
CvMat stubB, *imgB = (CvMat*)arrB;
CvSize imgSize;
float eps = (float)MIN(winSize.width, winSize.height);
- CV_CALL( imgA = cvGetMat( imgA, &stubA ));
- CV_CALL( imgB = cvGetMat( imgB, &stubB ));
+ imgA = cvGetMat( imgA, &stubA );
+ imgB = cvGetMat( imgB, &stubB );
if( CV_MAT_TYPE( imgA->type ) != CV_8UC1 )
- CV_ERROR( CV_StsUnsupportedFormat, "" );
+ CV_Error( CV_StsUnsupportedFormat, "" );
if( !CV_ARE_TYPES_EQ( imgA, imgB ))
- CV_ERROR( CV_StsUnmatchedFormats, "" );
+ CV_Error( CV_StsUnmatchedFormats, "" );
if( !CV_ARE_SIZES_EQ( imgA, imgB ))
- CV_ERROR( CV_StsUnmatchedSizes, "" );
+ CV_Error( CV_StsUnmatchedSizes, "" );
if( imgA->step != imgB->step )
- CV_ERROR( CV_StsUnmatchedSizes, "imgA and imgB must have equal steps" );
+ CV_Error( CV_StsUnmatchedSizes, "imgA and imgB must have equal steps" );
if( !matrices )
- CV_ERROR( CV_StsNullPtr, "" );
+ CV_Error( CV_StsNullPtr, "" );
imgSize = cvGetMatSize( imgA );
if( pyrA )
{
- CV_CALL( pyrA = cvGetMat( pyrA, &pstubA ));
+ pyrA = cvGetMat( pyrA, &pstubA );
if( pyrA->step*pyrA->height < icvMinimalPyramidSize( imgSize ) )
- CV_ERROR( CV_StsBadArg, "pyramid A has insufficient size" );
+ CV_Error( CV_StsBadArg, "pyramid A has insufficient size" );
}
else
{
if( pyrB )
{
- CV_CALL( pyrB = cvGetMat( pyrB, &pstubB ));
+ pyrB = cvGetMat( pyrB, &pstubB );
if( pyrB->step*pyrB->height < icvMinimalPyramidSize( imgSize ) )
- CV_ERROR( CV_StsBadArg, "pyramid B has insufficient size" );
+ CV_Error( CV_StsBadArg, "pyramid B has insufficient size" );
}
else
{
}
if( count == 0 )
- EXIT;
+ return;
/* check input arguments */
if( !featuresA || !featuresB || !matrices )
- CV_ERROR( CV_StsNullPtr, "" );
+ CV_Error( CV_StsNullPtr, "" );
if( winSize.width <= 1 || winSize.height <= 1 )
- CV_ERROR( CV_StsOutOfRange, "the search window is too small" );
+ CV_Error( CV_StsOutOfRange, "the search window is too small" );
if( count < 0 )
- CV_ERROR( CV_StsOutOfRange, "" );
+ CV_Error( CV_StsOutOfRange, "" );
- CV_CALL( icvInitPyramidalAlgorithm( imgA, imgB,
+ icvInitPyramidalAlgorithm( imgA, imgB,
pyrA, pyrB, level, &criteria, MAX_ITERS, flags,
- &imgI, &imgJ, &step, &size, &scale, &pyr_buffer ));
+ &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));
+ buffer.allocate(bufferBytes);
if( !status )
- CV_CALL( status = _status = (char*)cvAlloc(count) );
+ {
+ _status.allocate(count);
+ status = _status;
+ }
- patchI = (float *) buffer;
+ patchI = (float *)(uchar*)buffer;
patchJ = patchI + srcPatchLen;
Ix = patchJ + patchLen;
Iy = Ix + patchLen;
}
}
- icvTransformVector_64d( G, b, eta, 6, 6 );
+ for( k = 0; k < 6; k++ )
+ eta[k] = G[k*6]*b[0] + G[k*6+1]*b[1] + G[k*6+2]*b[2] +
+ G[k*6+3]*b[3] + G[k*6+4]*b[4] + G[k*6+5]*b[5];
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]);
}
}
}
-
- __END__;
-
- cvFree( &pyr_buffer );
- cvFree( &buffer );
- cvFree( &_status );
}
CV_IMPL int
-cvEstimateRigidTransform( const CvArr* _A, const CvArr* _B, CvMat* _M, int full_affine )
+cvEstimateRigidTransform( const CvArr* matA, const CvArr* matB, CvMat* matM, int full_affine )
{
- int result = 0;
-
- const int COUNT = 20;
+ const int COUNT = 15;
const int WIDTH = 160, HEIGHT = 120;
- const int RANSAC_MAX_ITERS = 100;
+ const int RANSAC_MAX_ITERS = 500;
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__;
+ cv::Ptr<CvMat> sA, sB;
+ cv::AutoBuffer<CvPoint2D32f> pA, pB;
+ cv::AutoBuffer<int> good_idx;
+ cv::AutoBuffer<char> status;
+ cv::Ptr<CvMat> gray;
- CvMat stubA, *A;
- CvMat stubB, *B;
+ CvMat stubA, *A = cvGetMat( matA, &stubA );
+ CvMat stubB, *B = cvGetMat( matB, &stubB );
CvSize sz0, sz1;
int cn, equal_sizes;
int i, j, k, k1;
- int count_x, count_y, count;
+ int count_x, count_y, count = 0;
double scale = 1;
CvRNG rng = cvRNG(-1);
double m[6]={0};
CvMat M = cvMat( 2, 3, CV_64F, m );
int good_count = 0;
+ CvRect brect;
- 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_IS_MAT(matM) )
+ CV_Error( matM ? 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" );
+ 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" );
+ 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 )
{
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 ));
+ sA = cvCreateMat( sz1.height, sz1.width, CV_8UC1 );
+ sB = cvCreateMat( sz1.height, sz1.width, CV_8UC1 );
- if( gray )
+ if( cn != 1 )
{
+ gray = cvCreateMat( sz0.height, sz0.width, CV_8UC1 );
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 );
+ gray.release();
}
else
{
- cvCvtColor( A, gray, CV_BGR2GRAY );
- cvResize( gray, sA, CV_INTER_AREA );
- cvCvtColor( B, gray, CV_BGR2GRAY );
+ cvResize( A, sA, CV_INTER_AREA );
+ cvResize( B, sB, CV_INTER_AREA );
}
-
- cvReleaseMat( &gray );
+
A = sA;
B = sB;
}
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]) ));
+ pA.allocate(count);
+ pB.allocate(count);
+ status.allocate(count);
for( i = 0, k = 0; i < count_y; i++ )
for( j = 0; j < count_x; j++, 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 );
- }
+ CvMat _pA, _pB;
+ pA.allocate(count);
+ pB.allocate(count);
+ _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_Error( CV_StsUnsupportedFormat, "Both input images must have either 8uC1 or 8uC3 type" );
- CV_CALL( good_idx = (int*)cvAlloc( count*sizeof(good_idx[0]) ));
+ good_idx.allocate(count);
if( count < RANSAC_SIZE0 )
- EXIT;
+ return 0;
+
+ CvMat _pB = cvMat(1, count, CV_32FC2, pB);
+ brect = cvBoundingRect(&_pB, 1);
// RANSAC stuff:
// 1. find the consensus
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 )
+ fabs(pA[idx[i]].y - pA[idx[j]].y) < FLT_EPSILON )
break;
if( fabs(pB[idx[i]].x - pB[idx[j]].x) +
- fabs(pB[idx[i]].y - pB[idx[j]].y) < MIN_TRIANGLE_SIDE )
+ fabs(pB[idx[i]].y - pB[idx[j]].y) < FLT_EPSILON )
break;
}
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 )
+
+ double dax1 = a[1].x - a[0].x, day1 = a[1].y - a[0].y;
+ double dax2 = a[2].x - a[0].x, day2 = a[2].y - a[0].y;
+ double dbx1 = b[1].x - b[0].y, dby1 = b[1].y - b[0].y;
+ double dbx2 = b[2].x - b[0].x, dby2 = b[2].y - b[0].y;
+ const double eps = 0.01;
+
+ if( fabs(dax1*day2 - day1*dax2) < eps*sqrt(dax1*dax1+day1*day1)*sqrt(dax2*dax2+day2*day2) ||
+ fabs(dbx1*dby2 - dby1*dbx2) < eps*sqrt(dbx1*dbx1+dby1*dby1)*sqrt(dbx2*dbx2+dby2*dby2) )
continue;
}
break;
// estimate the transformation using 3 points
icvGetRTMatrix( a, b, 3, &M, full_affine );
- for( i = 0; i < count; i++ )
+ 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 )
+ fabs( m[3]*pA[i].x + m[4]*pA[i].y + m[5] - pB[i].y ) < MAX(brect.width,brect.height)*0.05 )
good_idx[good_count++] = i;
}
}
if( k >= RANSAC_MAX_ITERS )
- EXIT;
+ return 0;
if( good_count < count )
{
icvGetRTMatrix( pA, pB, good_count, &M, full_affine );
m[2] /= scale;
m[5] /= scale;
- CV_CALL( cvConvert( &M, _M ));
- result = 1;
-
- __END__;
+ cvConvert( &M, matM );
+
+ return 1;
+}
- cvReleaseMat( &sA );
- cvReleaseMat( &sB );
- cvFree( &pA );
- cvFree( &pB );
- cvFree( &status );
- cvFree( &good_idx );
- cvReleaseMat( &gray );
+namespace cv
+{
- return result;
+Mat estimateRigidTransform( const Mat& A,
+ const Mat& B,
+ bool fullAffine )
+{
+ Mat M(2, 3, CV_64F);
+ CvMat matA = A, matB = B, matM = M;
+ cvEstimateRigidTransform(&matA, &matB, &matM, fullAffine);
+ return M;
+}
}
-
/* End of file. */
projects / opencv.git / blobdiff