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OpticalFlow.h
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#ifndef OPTICALFLOW_H_
#define OPTICALFLOW_H_
#include "Track.h"
#include <time.h>
using namespace cv;
namespace my
{
static void
FarnebackPolyExp( const Mat& src, Mat& dst, int n, double sigma )
{
int k, x, y;
assert( src.type() == CV_32FC1 );
int width = src.cols;
int height = src.rows;
AutoBuffer<float> kbuf(n*6 + 3), _row((width + n*2)*3);
float* g = kbuf + n;
float* xg = g + n*2 + 1;
float* xxg = xg + n*2 + 1;
float *row = (float*)_row + n*3;
if( sigma < FLT_EPSILON )
sigma = n*0.3;
double s = 0.;
for( x = -n; x <= n; x++ )
{
g[x] = (float)exp(-x*x/(2*sigma*sigma));
s += g[x];
}
s = 1./s;
for( x = -n; x <= n; x++ )
{
g[x] = (float)(g[x]*s);
xg[x] = (float)(x*g[x]);
xxg[x] = (float)(x*x*g[x]);
}
Mat_<double> G = Mat_<double>::zeros(6, 6);
for( y = -n; y <= n; y++ )
for( x = -n; x <= n; x++ )
{
G(0,0) += g[y]*g[x];
G(1,1) += g[y]*g[x]*x*x;
G(3,3) += g[y]*g[x]*x*x*x*x;
G(5,5) += g[y]*g[x]*x*x*y*y;
}
//G[0][0] = 1.;
G(2,2) = G(0,3) = G(0,4) = G(3,0) = G(4,0) = G(1,1);
G(4,4) = G(3,3);
G(3,4) = G(4,3) = G(5,5);
// invG:
// [ x e e ]
// [ y ]
// [ y ]
// [ e z ]
// [ e z ]
// [ u ]
Mat_<double> invG = G.inv(DECOMP_CHOLESKY);
double ig11 = invG(1,1), ig03 = invG(0,3), ig33 = invG(3,3), ig55 = invG(5,5);
dst.create( height, width, CV_32FC(5) );
for( y = 0; y < height; y++ )
{
float g0 = g[0], g1, g2;
float *srow0 = (float*)(src.data + src.step*y), *srow1 = 0;
float *drow = (float*)(dst.data + dst.step*y);
// vertical part of convolution
for( x = 0; x < width; x++ )
{
row[x*3] = srow0[x]*g0;
row[x*3+1] = row[x*3+2] = 0.f;
}
for( k = 1; k <= n; k++ )
{
g0 = g[k]; g1 = xg[k]; g2 = xxg[k];
srow0 = (float*)(src.data + src.step*max(y-k,0));
srow1 = (float*)(src.data + src.step*min(y+k,height-1));
for( x = 0; x < width; x++ )
{
float p = srow0[x] + srow1[x];
float t0 = row[x*3] + g0*p;
float t1 = row[x*3+1] + g1*(srow1[x] - srow0[x]);
float t2 = row[x*3+2] + g2*p;
row[x*3] = t0;
row[x*3+1] = t1;
row[x*3+2] = t2;
}
}
// horizontal part of convolution
for( x = 0; x < n*3; x++ )
{
row[-1-x] = row[2-x];
row[width*3+x] = row[width*3+x-3];
}
for( x = 0; x < width; x++ )
{
g0 = g[0];
// r1 ~ 1, r2 ~ x, r3 ~ y, r4 ~ x^2, r5 ~ y^2, r6 ~ xy
double b1 = row[x*3]*g0, b2 = 0, b3 = row[x*3+1]*g0,
b4 = 0, b5 = row[x*3+2]*g0, b6 = 0;
for( k = 1; k <= n; k++ )
{
double tg = row[(x+k)*3] + row[(x-k)*3];
g0 = g[k];
b1 += tg*g0;
b4 += tg*xxg[k];
b2 += (row[(x+k)*3] - row[(x-k)*3])*xg[k];
b3 += (row[(x+k)*3+1] + row[(x-k)*3+1])*g0;
b6 += (row[(x+k)*3+1] - row[(x-k)*3+1])*xg[k];
b5 += (row[(x+k)*3+2] + row[(x-k)*3+2])*g0;
}
// do not store r1
drow[x*5+1] = (float)(b2*ig11);
drow[x*5] = (float)(b3*ig11);
drow[x*5+3] = (float)(b1*ig03 + b4*ig33);
drow[x*5+2] = (float)(b1*ig03 + b5*ig33);
drow[x*5+4] = (float)(b6*ig55);
}
}
row -= n*3;
}
static void
FarnebackUpdateMatrices( const Mat& _R0, const Mat& _R1, const Mat& _flow, Mat& matM, int _y0, int _y1 )
{
const int BORDER = 5;
static const float border[BORDER] = {0.14f, 0.14f, 0.4472f, 0.4472f, 0.4472f};
int x, y, width = _flow.cols, height = _flow.rows;
const float* R1 = (float*)_R1.data;
size_t step1 = _R1.step/sizeof(R1[0]);
matM.create(height, width, CV_32FC(5));
for( y = _y0; y < _y1; y++ )
{
const float* flow = (float*)(_flow.data + y*_flow.step);
const float* R0 = (float*)(_R0.data + y*_R0.step);
float* M = (float*)(matM.data + y*matM.step);
for( x = 0; x < width; x++ )
{
float dx = flow[x*2], dy = flow[x*2+1];
float fx = x + dx, fy = y + dy;
int x1 = cvFloor(fx), y1 = cvFloor(fy);
const float* ptr = R1 + y1*step1 + x1*5;
float r2, r3, r4, r5, r6;
fx -= x1; fy -= y1;
if( (unsigned)x1 < (unsigned)(width-1) &&
(unsigned)y1 < (unsigned)(height-1) )
{
float a00 = (1.f-fx)*(1.f-fy), a01 = fx*(1.f-fy),
a10 = (1.f-fx)*fy, a11 = fx*fy;
r2 = a00*ptr[0] + a01*ptr[5] + a10*ptr[step1] + a11*ptr[step1+5];
r3 = a00*ptr[1] + a01*ptr[6] + a10*ptr[step1+1] + a11*ptr[step1+6];
r4 = a00*ptr[2] + a01*ptr[7] + a10*ptr[step1+2] + a11*ptr[step1+7];
r5 = a00*ptr[3] + a01*ptr[8] + a10*ptr[step1+3] + a11*ptr[step1+8];
r6 = a00*ptr[4] + a01*ptr[9] + a10*ptr[step1+4] + a11*ptr[step1+9];
r4 = (R0[x*5+2] + r4)*0.5f;
r5 = (R0[x*5+3] + r5)*0.5f;
r6 = (R0[x*5+4] + r6)*0.25f;
}
else
{
r2 = r3 = 0.f;
r4 = R0[x*5+2];
r5 = R0[x*5+3];
r6 = R0[x*5+4]*0.5f;
}
r2 = (R0[x*5] - r2)*0.5f;
r3 = (R0[x*5+1] - r3)*0.5f;
r2 += r4*dy + r6*dx;
r3 += r6*dy + r5*dx;
if( (unsigned)(x - BORDER) >= (unsigned)(width - BORDER*2) ||
(unsigned)(y - BORDER) >= (unsigned)(height - BORDER*2))
{
float scale = (x < BORDER ? border[x] : 1.f)*
(x >= width - BORDER ? border[width - x - 1] : 1.f)*
(y < BORDER ? border[y] : 1.f)*
(y >= height - BORDER ? border[height - y - 1] : 1.f);
r2 *= scale; r3 *= scale; r4 *= scale;
r5 *= scale; r6 *= scale;
}
M[x*5] = r4*r4 + r6*r6; // G(1,1)
M[x*5+1] = (r4 + r5)*r6; // G(1,2)=G(2,1)
M[x*5+2] = r5*r5 + r6*r6; // G(2,2)
M[x*5+3] = r4*r2 + r6*r3; // h(1)
M[x*5+4] = r6*r2 + r5*r3; // h(2)
}
}
}
static void
FarnebackUpdateFlow_GaussianBlur( const Mat& _R0, const Mat& _R1,
Mat& _flow, Mat& matM, int block_size,
bool update_matrices )
{
int x, y, i, width = _flow.cols, height = _flow.rows;
int m = block_size/2;
int y0 = 0, y1;
int min_update_stripe = max((1 << 10)/width, block_size);
double sigma = m*0.3, s = 1;
AutoBuffer<float> _vsum((width+m*2+2)*5 + 16), _hsum(width*5 + 16);
AutoBuffer<float, 4096> _kernel((m+1)*5 + 16);
AutoBuffer<float*, 1024> _srow(m*2+1);
float *vsum = alignPtr((float*)_vsum + (m+1)*5, 16), *hsum = alignPtr((float*)_hsum, 16);
float* kernel = (float*)_kernel;
const float** srow = (const float**)&_srow[0];
kernel[0] = (float)s;
for( i = 1; i <= m; i++ )
{
float t = (float)exp(-i*i/(2*sigma*sigma) );
kernel[i] = t;
s += t*2;
}
s = 1./s;
for( i = 0; i <= m; i++ )
kernel[i] = (float)(kernel[i]*s);
#if CV_SSE2
float* simd_kernel = alignPtr(kernel + m+1, 16);
volatile bool useSIMD = checkHardwareSupport(CV_CPU_SSE);
if( useSIMD )
{
for( i = 0; i <= m; i++ )
_mm_store_ps(simd_kernel + i*4, _mm_set1_ps(kernel[i]));
}
#endif
// compute blur(G)*flow=blur(h)
for( y = 0; y < height; y++ )
{
double g11, g12, g22, h1, h2;
float* flow = (float*)(_flow.data + _flow.step*y);
// vertical blur
for( i = 0; i <= m; i++ )
{
srow[m-i] = (const float*)(matM.data + matM.step*max(y-i,0));
srow[m+i] = (const float*)(matM.data + matM.step*min(y+i,height-1));
}
x = 0;
#if CV_SSE2
if( useSIMD )
{
for( ; x <= width*5 - 16; x += 16 )
{
const float *sptr0 = srow[m], *sptr1;
__m128 g4 = _mm_load_ps(simd_kernel);
__m128 s0, s1, s2, s3;
s0 = _mm_mul_ps(_mm_loadu_ps(sptr0 + x), g4);
s1 = _mm_mul_ps(_mm_loadu_ps(sptr0 + x + 4), g4);
s2 = _mm_mul_ps(_mm_loadu_ps(sptr0 + x + 8), g4);
s3 = _mm_mul_ps(_mm_loadu_ps(sptr0 + x + 12), g4);
for( i = 1; i <= m; i++ )
{
__m128 x0, x1;
sptr0 = srow[m+i], sptr1 = srow[m-i];
g4 = _mm_load_ps(simd_kernel + i*4);
x0 = _mm_add_ps(_mm_loadu_ps(sptr0 + x), _mm_loadu_ps(sptr1 + x));
x1 = _mm_add_ps(_mm_loadu_ps(sptr0 + x + 4), _mm_loadu_ps(sptr1 + x + 4));
s0 = _mm_add_ps(s0, _mm_mul_ps(x0, g4));
s1 = _mm_add_ps(s1, _mm_mul_ps(x1, g4));
x0 = _mm_add_ps(_mm_loadu_ps(sptr0 + x + 8), _mm_loadu_ps(sptr1 + x + 8));
x1 = _mm_add_ps(_mm_loadu_ps(sptr0 + x + 12), _mm_loadu_ps(sptr1 + x + 12));
s2 = _mm_add_ps(s2, _mm_mul_ps(x0, g4));
s3 = _mm_add_ps(s3, _mm_mul_ps(x1, g4));
}
_mm_store_ps(vsum + x, s0);
_mm_store_ps(vsum + x + 4, s1);
_mm_store_ps(vsum + x + 8, s2);
_mm_store_ps(vsum + x + 12, s3);
}
for( ; x <= width*5 - 4; x += 4 )
{
const float *sptr0 = srow[m], *sptr1;
__m128 g4 = _mm_load_ps(simd_kernel);
__m128 s0 = _mm_mul_ps(_mm_loadu_ps(sptr0 + x), g4);
for( i = 1; i <= m; i++ )
{
sptr0 = srow[m+i], sptr1 = srow[m-i];
g4 = _mm_load_ps(simd_kernel + i*4);
__m128 x0 = _mm_add_ps(_mm_loadu_ps(sptr0 + x), _mm_loadu_ps(sptr1 + x));
s0 = _mm_add_ps(s0, _mm_mul_ps(x0, g4));
}
_mm_store_ps(vsum + x, s0);
}
}
#endif
for( ; x < width*5; x++ )
{
float s0 = srow[m][x]*kernel[0];
for( i = 1; i <= m; i++ )
s0 += (srow[m+i][x] + srow[m-i][x])*kernel[i];
vsum[x] = s0;
}
// update borders
for( x = 0; x < m*5; x++ )
{
vsum[-1-x] = vsum[4-x];
vsum[width*5+x] = vsum[width*5+x-5];
}
// horizontal blur
x = 0;
#if CV_SSE2
if( useSIMD )
{
for( ; x <= width*5 - 8; x += 8 )
{
__m128 g4 = _mm_load_ps(simd_kernel);
__m128 s0 = _mm_mul_ps(_mm_loadu_ps(vsum + x), g4);
__m128 s1 = _mm_mul_ps(_mm_loadu_ps(vsum + x + 4), g4);
for( i = 1; i <= m; i++ )
{
g4 = _mm_load_ps(simd_kernel + i*4);
__m128 x0 = _mm_add_ps(_mm_loadu_ps(vsum + x - i*5),
_mm_loadu_ps(vsum + x + i*5));
__m128 x1 = _mm_add_ps(_mm_loadu_ps(vsum + x - i*5 + 4),
_mm_loadu_ps(vsum + x + i*5 + 4));
s0 = _mm_add_ps(s0, _mm_mul_ps(x0, g4));
s1 = _mm_add_ps(s1, _mm_mul_ps(x1, g4));
}
_mm_store_ps(hsum + x, s0);
_mm_store_ps(hsum + x + 4, s1);
}
}
#endif
for( ; x < width*5; x++ )
{
float sum = vsum[x]*kernel[0];
for( i = 1; i <= m; i++ )
sum += kernel[i]*(vsum[x - i*5] + vsum[x + i*5]);
hsum[x] = sum;
}
for( x = 0; x < width; x++ )
{
g11 = hsum[x*5];
g12 = hsum[x*5+1];
g22 = hsum[x*5+2];
h1 = hsum[x*5+3];
h2 = hsum[x*5+4];
double idet = 1./(g11*g22 - g12*g12 + 1e-3);
flow[x*2] = (float)((g11*h2-g12*h1)*idet);
flow[x*2+1] = (float)((g22*h1-g12*h2)*idet);
}
y1 = y == height - 1 ? height : y - block_size;
if( update_matrices && (y1 == height || y1 >= y0 + min_update_stripe) )
{
FarnebackUpdateMatrices( _R0, _R1, _flow, matM, y0, y1 );
y0 = y1;
}
}
}
// in-place median blur for optical flow
void MedianBlurFlow(Mat& flow, const int ksize)
{
Mat channels[2];
split(flow, channels);
medianBlur(channels[0], channels[0], ksize);
medianBlur(channels[1], channels[1], ksize);
merge(channels, 2, flow);
}
void FarnebackPolyExpPyr(const Mat& img, vector<Mat>& poly_exp_pyr,
vector<float>& fscales, int poly_n, double poly_sigma)
{
Mat fimg;
for(int k = 0; k < poly_exp_pyr.size(); k++)
{
double sigma = (fscales[k]-1)*0.5;
int smooth_sz = cvRound(sigma*5)|1;
smooth_sz = max(smooth_sz, 3);
int width = poly_exp_pyr[k].cols;
int height = poly_exp_pyr[k].rows;
Mat R, I;
img.convertTo(fimg, CV_32F);
//printf("sigma=%f smooth_sz=%f\n",sigma,smooth_sz);
GaussianBlur(fimg, fimg, Size(smooth_sz, smooth_sz), sigma, sigma);
resize(fimg, I, Size(width, height), CV_INTER_LINEAR);
FarnebackPolyExp(I, R, poly_n, poly_sigma);
R.copyTo(poly_exp_pyr[k]);
}
}
void FarnebackPolyExpPyr_cv(const Mat& img, vector<Mat>& poly_exp_pyr,
vector<float>& fscales, int poly_n, double poly_sigma)
{
Mat fimg;
for(int k = 0; k < poly_exp_pyr.size(); k++)
{
double sigma = (fscales[k]-1)*0.5;
int smooth_sz = cvRound(sigma*5)|1;
smooth_sz = max(smooth_sz, 3);
int width = poly_exp_pyr[k].cols;
int height = poly_exp_pyr[k].rows;
Mat I;
img.convertTo(fimg, CV_32F);
GaussianBlur(fimg, fimg, Size(smooth_sz, smooth_sz), sigma, sigma);
resize(fimg, I, Size(width, height), CV_INTER_LINEAR);
printf("[INFO] I ch=%d\n",I.channels());
I.copyTo(poly_exp_pyr[k]);
}
}
void calcOpticalFlowFarneback(vector<Mat>& prev_poly_exp_pyr, vector<Mat>& poly_exp_pyr,
vector<Mat>& flow_pyr, int winsize, int iterations)
{
int i, k;
Mat prevFlow, flow;
for( k = flow_pyr.size() - 1; k >= 0; k-- )
{
int width = flow_pyr[k].cols;
int height = flow_pyr[k].rows;
flow.create( height, width, CV_32FC2 );
if( !prevFlow.data )
flow = Mat::zeros( height, width, CV_32FC2 );
else {
resize( prevFlow, flow, Size(width, height), 0, 0, INTER_LINEAR );
flow *= scale_stride;
}
Mat R[2], M;
prev_poly_exp_pyr[k].copyTo(R[0]);
poly_exp_pyr[k].copyTo(R[1]);
FarnebackUpdateMatrices( R[0], R[1], flow, M, 0, flow.rows );
for( i = 0; i < iterations; i++ )
FarnebackUpdateFlow_GaussianBlur( R[0], R[1], flow, M, winsize, i < iterations - 1 );
MedianBlurFlow(flow, 5);
prevFlow = flow;
flow.copyTo(flow_pyr[k]);
}
}
}
#endif /*OPTICALFLOW_H_*/