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features_lookup.cc
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features_lookup.cc
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// Original Code by Pedro Felzenszwalb
// Modified by Michael and Bram to do computation
// lookups.
//
#include <math.h>
#include "mex.h"
#include "util.h"
// small value, used to avoid division by zero
#define eps 0.0001
// unit vectors used to compute gradient orientation
double uu[9] = {1.0000,
0.9397,
0.7660,
0.500,
0.1736,
-0.1736,
-0.5000,
-0.7660,
-0.9397};
double vv[9] = {0.0000,
0.3420,
0.6428,
0.8660,
0.9848,
0.9848,
0.8660,
0.6428,
0.3420};
// int best_o_lookup[512][512];
#include "best_o_lookup_old.h"
static inline double min(double x, double y) { return (x <= y ? x : y); }
static inline double max(double x, double y) { return (x <= y ? y : x); }
static inline int min(int x, int y) { return (x <= y ? x : y); }
static inline int max(int x, int y) { return (x <= y ? y : x); }
// main function:
// takes a double color image and a bin size
// returns HOG features
mxArray *process(const mxArray *mximage, const mxArray *mxsbin) {
double *im = (double *)mxGetPr(mximage);
const int *dims = mxGetDimensions(mximage);
if (mxGetNumberOfDimensions(mximage) != 3 ||
dims[2] != 3 ||
mxGetClassID(mximage) != mxDOUBLE_CLASS)
mexErrMsgTxt("Invalid input");
int sbin = (int)mxGetScalar(mxsbin);
// memory for caching orientation histograms & their norms
int blocks[2];
blocks[0] = (int)round((double)dims[0]/(double)sbin);
blocks[1] = (int)round((double)dims[1]/(double)sbin);
double *hist = (double *)mxCalloc(blocks[0]*blocks[1]*18, sizeof(double));
double *norm = (double *)mxCalloc(blocks[0]*blocks[1], sizeof(double));
// memory for HOG features
int out[3];
out[0] = max(blocks[0]-2, 0);
out[1] = max(blocks[1]-2, 0);
out[2] = 27+4;
mxArray *mxfeat = mxCreateNumericArray(3, out, mxDOUBLE_CLASS, mxREAL);
double *feat = (double *)mxGetPr(mxfeat);
int visible[2];
visible[0] = blocks[0]*sbin;
visible[1] = blocks[1]*sbin;
for (int x = 1; x < visible[1]-1; x++) {
for (int y = 1; y < visible[0]-1; y++) {
// first color channel
double *s = im + min(x, dims[1]-2)*dims[0] + min(y, dims[0]-2);
double dy = *(s+1) - *(s-1);
double dx = *(s+dims[0]) - *(s-dims[0]);
double v = dx*dx + dy*dy;
// second color channel
s += dims[0]*dims[1];
double dy2 = *(s+1) - *(s-1);
double dx2 = *(s+dims[0]) - *(s-dims[0]);
double v2 = dx2*dx2 + dy2*dy2;
// third color channel
s += dims[0]*dims[1];
double dy3 = *(s+1) - *(s-1);
double dx3 = *(s+dims[0]) - *(s-dims[0]);
double v3 = dx3*dx3 + dy3*dy3;
// pick channel with strongest gradient
if (v2 > v) {
v = v2;
dx = dx2;
dy = dy2;
}
if (v3 > v) {
v = v3;
dx = dx3;
dy = dy3;
}
// snap to one of 18 orientations
//double best_dot = 0;
//int best_o = 0;
//for (int o = 0; o < 9; o++) {
// double dot = uu[o]*dx + vv[o]*dy;
// if (dot > best_dot) {
// best_dot = dot;
// best_o = o;
// } else if (-dot > best_dot) {
// best_dot = -dot;
// best_o = o+9;
// }
//}
int lookup_x = (int)(511*dx)+511;
ASSERT(lookup_x >= 0 && lookup_x < 1023);
int lookup_y = (int)(511*dy)+511;
ASSERT(lookup_y >= 0 && lookup_y < 1023);
int best_o = best_o_lookup[lookup_x][lookup_y];
// add to 4 histograms around pixel using linear interpolation
double xp = ((double)x+0.5)/(double)sbin - 0.5;
double yp = ((double)y+0.5)/(double)sbin - 0.5;
int ixp = (int)floor(xp);
int iyp = (int)floor(yp);
double vx0 = xp-ixp;
double vy0 = yp-iyp;
double vx1 = 1.0-vx0;
double vy1 = 1.0-vy0;
v = sqrt(v);
if (ixp >= 0 && iyp >= 0) {
*(hist + ixp*blocks[0] + iyp + best_o*blocks[0]*blocks[1]) +=
vx1*vy1*v;
}
if (ixp+1 < blocks[1] && iyp >= 0) {
*(hist + (ixp+1)*blocks[0] + iyp + best_o*blocks[0]*blocks[1]) +=
vx0*vy1*v;
}
if (ixp >= 0 && iyp+1 < blocks[0]) {
*(hist + ixp*blocks[0] + (iyp+1) + best_o*blocks[0]*blocks[1]) +=
vx1*vy0*v;
}
if (ixp+1 < blocks[1] && iyp+1 < blocks[0]) {
*(hist + (ixp+1)*blocks[0] + (iyp+1) + best_o*blocks[0]*blocks[1]) +=
vx0*vy0*v;
}
}
}
// compute energy in each block by summing over orientations
for (int o = 0; o < 9; o++) {
double *src1 = hist + o*blocks[0]*blocks[1];
double *src2 = hist + (o+9)*blocks[0]*blocks[1];
double *dst = norm;
double *end = norm + blocks[1]*blocks[0];
while (dst < end) {
*(dst++) += (*src1 + *src2) * (*src1 + *src2);
src1++;
src2++;
}
}
// compute features
for (int x = 0; x < out[1]; x++) {
for (int y = 0; y < out[0]; y++) {
double *dst = feat + x*out[0] + y;
double *src, *p, n1, n2, n3, n4;
p = norm + (x+1)*blocks[0] + y+1;
n1 = 1.0 / sqrt(*p + *(p+1) + *(p+blocks[0]) + *(p+blocks[0]+1) + eps);
p = norm + (x+1)*blocks[0] + y;
n2 = 1.0 / sqrt(*p + *(p+1) + *(p+blocks[0]) + *(p+blocks[0]+1) + eps);
p = norm + x*blocks[0] + y+1;
n3 = 1.0 / sqrt(*p + *(p+1) + *(p+blocks[0]) + *(p+blocks[0]+1) + eps);
p = norm + x*blocks[0] + y;
n4 = 1.0 / sqrt(*p + *(p+1) + *(p+blocks[0]) + *(p+blocks[0]+1) + eps);
double t1 = 0;
double t2 = 0;
double t3 = 0;
double t4 = 0;
// contrast-sensitive features
src = hist + (x+1)*blocks[0] + (y+1);
for (int o = 0; o < 18; o++) {
double h1 = min(*src * n1, 0.2);
double h2 = min(*src * n2, 0.2);
double h3 = min(*src * n3, 0.2);
double h4 = min(*src * n4, 0.2);
*dst = 0.5 * (h1 + h2 + h3 + h4);
t1 += h1;
t2 += h2;
t3 += h3;
t4 += h4;
dst += out[0]*out[1];
src += blocks[0]*blocks[1];
}
// contrast-insensitive features
src = hist + (x+1)*blocks[0] + (y+1);
for (int o = 0; o < 9; o++) {
double sum = *src + *(src + 9*blocks[0]*blocks[1]);
double h1 = min(sum * n1, 0.2);
double h2 = min(sum * n2, 0.2);
double h3 = min(sum * n3, 0.2);
double h4 = min(sum * n4, 0.2);
*dst = 0.5 * (h1 + h2 + h3 + h4);
dst += out[0]*out[1];
src += blocks[0]*blocks[1];
}
// texture features
*dst = 0.2357 * t1;
dst += out[0]*out[1];
*dst = 0.2357 * t2;
dst += out[0]*out[1];
*dst = 0.2357 * t3;
dst += out[0]*out[1];
*dst = 0.2357 * t4;
}
}
mxFree(hist);
mxFree(norm);
return mxfeat;
}
// matlab entry point
// F = features_pedro(image, bin)
// image should be color with double values
void mexFunction(int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[]) {
if (nrhs != 2)
mexErrMsgTxt("Wrong number of inputs");
if (nlhs != 1)
mexErrMsgTxt("Wrong number of outputs");
plhs[0] = process(prhs[0], prhs[1]);
}