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dali_dist.c
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dali_dist.c
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/**
* DaLI: Deformation and Light Invariant Descriptor
* Edgar Simo-Serra, Carme Torras, Francesc Moreno-Noguer
* International Journal of Computer Vision (IJCV), 2015
*
* Copyright (C) <2011-2015> <Francesc Moreno-Noguer, Edgar Simo-Serra>
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the version 3 of the GNU General Public License
* as published by the Free Software Foundation.
*
* This program is distributed in the hope that it will be useful, but
* WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* General Public License for more details.
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*
* Edgar Simo-Serra, Institut de Robotica i Informatica Industrial (CSIC/UPC)
* [email protected], http://www-iri.upc.es/people/esimo/
**/
#include "dali.h"
#include <math.h>
#include <stdio.h>
#include <assert.h>
#define MIN(a,b) (((a)<(b))?(a):(b))
#define POW2(x) ((x)*(x))
static void dali_updateGauss( dali_t *desc, double sigma )
{
int i;
double s;
if (fabs(sigma - *desc->sigma) < 1e-10)
return;
s = 2.*POW2( (double)desc->sz * sigma );
for (i=0; i<desc->len; i++)
desc->sgauss[ i ] = exp( desc->gauss[ i ] / s );
*desc->sigma = sigma;
}
double dali_distance( dali_t *desc1, dali_t *desc2, double sigma )
{
int i,w;
int ws;
double d1, d2, dd, d, dr;
double g, gs;
/* Set up sizes. */
assert( desc1->sz == desc2->sz );
assert( desc1->len == desc2->len );
/* Update gaussians if necessary. */
dali_updateGauss( desc1, sigma );
/* Set up offsets to prepare comparison. */
ws = MIN( desc1->wlen, desc2->wlen );
/* Calculate distance for the subset we've found. */
gs = 0.;
d = 0.;
for (i=0; i<desc1->len; i++) {
/* Check if in mask. */
if (desc1->mask[ i ] == 0)
continue;
if (desc2->mask[ i ] == 0)
continue;
/* Calculate Gaussian at the given position. */
g = desc1->sgauss[ i ] ;
/* Increment Gaussian size. */
gs += g;
/* Inner loop in frequency domain has same Gaussian value. */
dr = 0.;
for (w=0; w<ws; w++) {
d1 = desc1->desc[ i*desc1->wlen + w ];
d2 = desc2->desc[ i*desc2->wlen + w ];
dd = d1-d2;
dr += dd*dd;
}
/* We modulate the square by the Gaussian so it's a weighted sum. */
d += g * dr;
}
if (gs == 0.)
d = NAN;
else
d /= gs;
return d;
}
double dali_distance_transform( dali_t *desc1, dali_t *desc2,
double sigma, double theta, double scale )
{
int u,v,w;
int ue,ve;
int urot, vrot;
int ws;
double ud, vd;
double d1, d2, dd, d, dr;
double g, gs;
double cR, sR;
double w2, h2;
int id1, id2;
/* Set up sizes. */
assert( desc1->sz == desc2->sz );
assert( desc1->len == desc2->len );
/* Update gaussians if necessary. */
dali_updateGauss( desc1, sigma );
/* Set up offsets to prepare comparison. */
ue = desc1->ulen;
ve = desc1->vlen;
ws = MIN( desc1->wlen, desc2->wlen );
/* Prepare rotation. */
cR = cos( theta );
sR = sin( theta );
w2 = (double)ue/2.;
h2 = (double)ve/2.;
/* Calculate distance for the subset we've found. */
gs = 0.;
d = 0.;
for (u=0; u<ue; u++) {
for (v=0; v<ve; v++) {
/* Get first ID and check to see if it's in mask. */
id1 = desc1->shape[ u*ve + v ];
if (id1 < 0)
continue;
if (desc1->mask[ id1 ] == 0)
continue;
/* We'll rotate around for the second one. */
ud = (double)u;
vd = (double)v;
urot = (int)round( (w2 + (ud - w2)*cR + (vd - h2)*sR)/scale );
vrot = (int)round( (h2 - (ud - w2)*sR + (vd - h2)*cR)/scale );
/* Make sure it's in the mask of the second one. */
if ((urot < 0) || (urot >= desc2->ulen))
continue;
if ((vrot < 0) || (vrot >= desc2->vlen))
continue;
id2 = desc2->shape[ urot*ve + vrot ];
if (id2 < 0)
continue;
if (desc2->mask[ id2 ] == 0)
continue;
/* Calculate Gaussian at the given position. */
g = desc1->sgauss[ id1 ];
/* Increment Gaussian size. */
gs += g;
/* Inner loop in frequency domain has same Gaussian value. */
dr = 0.;
for (w=0; w<ws; w++) {
d1 = desc1->desc[ id1*desc1->wlen + w ];
d2 = desc2->desc[ id2*desc2->wlen + w ];
dd = d1-d2;
dr += dd*dd;
}
/* We modulate the square by the Gaussian so it's a weighted sum. */
d += g * dr;
}
}
if (gs == 0.)
d = NAN;
else
d /= gs;
return d;
}
double dali_distance_transform_lin( dali_t *desc1, dali_t *desc2,
double sigma, double theta, double scale )
{
int u,v,w;
int ue,ve;
double urot, vrot;
double ua,va, u1a,v1a, uva,u1va,uv1a,u1v1a;
int url,uru, vrl,vru;
int ws;
double ud, vd;
double d1, d2, dd, d, dr;
double g, gs;
double cR, sR;
double w2, h2;
int id1, id2ll, id2lu, id2uu, id2ul;
/* Set up sizes. */
assert( desc1->sz == desc2->sz );
assert( desc1->len == desc2->len );
/* Set up offsets to prepare comparison. */
ue = desc1->ulen;
ve = desc1->vlen;
ws = MIN( desc1->wlen, desc2->wlen );
/* Prepare rotation. */
cR = cos( theta );
sR = sin( theta );
w2 = (double)ue/2.;
h2 = (double)ve/2.;
/* Update gaussians if necessary. */
dali_updateGauss( desc1, sigma );
/* Calculate distance for the subset we've found. */
gs = 0.;
d = 0.;
for (u=0; u<ue; u++) {
for (v=0; v<ve; v++) {
/* Get first ID and check to see if it's in mask. */
id1 = desc1->shape[ u*ve + v ];
if (id1 < 0)
continue;
if (desc1->mask[ id1 ] == 0)
continue;
/* We'll rotate around for the second one. */
ud = (double)u;
vd = (double)v;
urot = (w2 + (ud - w2)*cR + (vd - h2)*sR) / scale;
vrot = (h2 - (ud - w2)*sR + (vd - h2)*cR) / scale;
url = floor( urot );
uru = ceil( urot );
vrl = floor( vrot );
vru = ceil( vrot );
/* Make sure it's in the maks of the second one. */
if ((url < 0) || (uru >= desc2->ulen))
continue;
if ((vrl < 0) || (vru >= desc2->vlen))
continue;
id2ll = desc2->shape[ url*ve + vrl ];
id2lu = desc2->shape[ url*ve + vru ];
id2uu = desc2->shape[ uru*ve + vru ];
id2ul = desc2->shape[ uru*ve + vrl ];
if ((id2ll < 0) || (id2lu < 0) || (id2uu < 0) || (id2ul < 0))
continue;
if (desc2->mask[ id2ll ] == 0)
continue;
if (desc2->mask[ id2lu ] == 0)
continue;
if (desc2->mask[ id2uu ] == 0)
continue;
if (desc2->mask[ id2ul ] == 0)
continue;
/* Calculate Gaussian at the given position. */
g = desc1->sgauss[ id1 ];
/* Increment Gaussian size. */
gs += g;
/* Some minor optimizations when calculating pixel weights. */
ua = urot - (double)url;
va = vrot - (double)vrl;
u1a = 1. - ua;
v1a = 1. - va;
uva = ua*va;
u1va = ua*v1a;
uv1a = u1a*va;
u1v1a = u1a*v1a;
/* Inner loop in frequency domain has same Gaussian value. */
dr = 0.;
for (w=0; w<ws; w++) {
d1 = desc1->desc[ id1*desc1->wlen + w ];
/* We must weigh by the transformation. */
d2 = uva * desc2->desc[ id2ll*desc2->wlen + w ] +
u1va * desc2->desc[ id2ul*desc2->wlen + w ] +
uv1a * desc2->desc[ id2lu*desc2->wlen + w ] +
u1v1a * desc2->desc[ id2uu*desc2->wlen + w ];
/* Calculate differences. */
dd = d1-d2;
dr += dd*dd;
}
/* We modulate the square by the Gaussian so it's a weighted sum. */
d += g * dr;
}
}
if (gs == 0.)
d = NAN;
else
d /= gs;
return d;
}
double dali_distance_pure( dali_t *desc1, dali_t *desc2 )
{
int i,w;
int ws;
double d1, d2, dd, d, dr;
/* Set up sizes. */
assert( desc1->sz == desc2->sz );
assert( desc1->len == desc2->len );
/* Set up offsets to prepare comparison. */
ws = MIN( desc1->wlen, desc2->wlen );
/* Calculate distance for the subset we've found. */
d = 0.;
for (i=0; i<desc1->len; i++) {
/* Inner loop in frequency domain has same Gaussian value. */
dr = 0.;
for (w=0; w<ws; w++) {
d1 = desc1->desc[ i*desc1->wlen + w ];
d2 = desc2->desc[ i*desc2->wlen + w ];
dd = d1-d2;
dr += dd*dd;
}
/* We modulate the square by the Gaussian so it's a weighted sum. */
d += dr;
}
return d;
}