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#include "_cv.h"
#include <float.h>
#include <stdio.h>
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;
}
}
}
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 )
{
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++ )
{
_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__;
if( ipp_optflow_state )
icvOpticalFlowPyrLKFree_8u_C1R_p( ipp_optflow_state );
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;
}
/* End of file. */