/*
* Copyright (C) 2011 The Android Open Source Project
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
/* $Id: db_metrics.h,v 1.3 2011/06/17 14:03:31 mbansal Exp $ */
#ifndef DB_METRICS
#define DB_METRICS
/*****************************************************************
* Lean and mean begins here *
*****************************************************************/
#include "db_utilities.h"
/*!
* \defgroup LMMetrics (LM) Metrics
*/
/*\{*/
/*!
Compute function value fp and Jacobian J of robustifier given input value f*/
inline void db_CauchyDerivative(double J[4],double fp[2],const double f[2],double one_over_scale2)
{
double x2,y2,r,r2,r2s,one_over_r2,fu,r_fu,one_over_r_fu;
double one_plus_r2s,half_dfu_dx,half_dfu_dy,coeff,coeff2,coeff3;
int at_zero;
/*The robustifier takes the input (x,y) and makes a new
vector (xp,yp) where
xp=sqrt(log(1+(x^2+y^2)*one_over_scale2))*x/sqrt(x^2+y^2)
yp=sqrt(log(1+(x^2+y^2)*one_over_scale2))*y/sqrt(x^2+y^2)
The new vector has the property
xp^2+yp^2=log(1+(x^2+y^2)*one_over_scale2)
i.e. when it is square-summed it gives the robust
reprojection error
Define
r2=(x^2+y^2) and
r2s=r2*one_over_scale2
fu=log(1+r2s)/r2
then
xp=sqrt(fu)*x
yp=sqrt(fu)*y
and
d(r2)/dx=2x
d(r2)/dy=2y
and
dfu/dx=d(r2)/dx*(r2s/(1+r2s)-log(1+r2s))/(r2*r2)
dfu/dy=d(r2)/dy*(r2s/(1+r2s)-log(1+r2s))/(r2*r2)
and
d(xp)/dx=1/(2sqrt(fu))*(dfu/dx)*x+sqrt(fu)
d(xp)/dy=1/(2sqrt(fu))*(dfu/dy)*x
d(yp)/dx=1/(2sqrt(fu))*(dfu/dx)*y
d(yp)/dy=1/(2sqrt(fu))*(dfu/dy)*y+sqrt(fu)
*/
x2=db_sqr(f[0]);
y2=db_sqr(f[1]);
r2=x2+y2;
r=sqrt(r2);
if(r2<=0.0) at_zero=1;
else
{
one_over_r2=1.0/r2;
r2s=r2*one_over_scale2;
one_plus_r2s=1.0+r2s;
fu=log(one_plus_r2s)*one_over_r2;
r_fu=sqrt(fu);
if(r_fu<=0.0) at_zero=1;
else
{
one_over_r_fu=1.0/r_fu;
fp[0]=r_fu*f[0];
fp[1]=r_fu*f[1];
/*r2s is always >= 0*/
coeff=(r2s/one_plus_r2s*one_over_r2-fu)*one_over_r2;
half_dfu_dx=f[0]*coeff;
half_dfu_dy=f[1]*coeff;
coeff2=one_over_r_fu*half_dfu_dx;
coeff3=one_over_r_fu*half_dfu_dy;
J[0]=coeff2*f[0]+r_fu;
J[1]=coeff3*f[0];
J[2]=coeff2*f[1];
J[3]=coeff3*f[1]+r_fu;
at_zero=0;
}
}
if(at_zero)
{
/*Close to zero the robustifying mapping
becomes identity*sqrt(one_over_scale2)*/
fp[0]=0.0;
fp[1]=0.0;
J[0]=sqrt(one_over_scale2);
J[1]=0.0;
J[2]=0.0;
J[3]=J[0];
}
}
inline double db_SquaredReprojectionErrorHomography(const double y[2],const double H[9],const double x[3])
{
double x0,x1,x2,mult;
double sd;
x0=H[0]*x[0]+H[1]*x[1]+H[2]*x[2];
x1=H[3]*x[0]+H[4]*x[1]+H[5]*x[2];
x2=H[6]*x[0]+H[7]*x[1]+H[8]*x[2];
mult=1.0/((x2!=0.0)?x2:1.0);
sd=db_sqr((y[0]-x0*mult))+db_sqr((y[1]-x1*mult));
return(sd);
}
inline double db_SquaredInhomogenousHomographyError(const double y[2],const double H[9],const double x[2])
{
double x0,x1,x2,mult;
double sd;
x0=H[0]*x[0]+H[1]*x[1]+H[2];
x1=H[3]*x[0]+H[4]*x[1]+H[5];
x2=H[6]*x[0]+H[7]*x[1]+H[8];
mult=1.0/((x2!=0.0)?x2:1.0);
sd=db_sqr((y[0]-x0*mult))+db_sqr((y[1]-x1*mult));
return(sd);
}
/*!
Return a constant divided by likelihood of a Cauchy distributed
reprojection error given the image point y, homography H, image point
point x and the squared scale coefficient one_over_scale2=1.0/(scale*scale)
where scale is the half width at half maximum (hWahM) of the
Cauchy distribution*/
inline double db_ExpCauchyInhomogenousHomographyError(const double y[2],const double H[9],const double x[2],
double one_over_scale2)
{
double sd;
sd=db_SquaredInhomogenousHomographyError(y,H,x);
return(1.0+sd*one_over_scale2);
}
/*!
Compute residual vector f between image point y and homography Hx of
image point x. Also compute Jacobian of f with respect
to an update dx of H*/
inline void db_DerivativeInhomHomographyError(double Jf_dx[18],double f[2],const double y[2],const double H[9],
const double x[2])
{
double xh,yh,zh,mult,mult2,xh_mult2,yh_mult2;
/*The Jacobian of the inhomogenous coordinates with respect to
the homogenous is
[1/zh 0 -xh/(zh*zh)]
[ 0 1/zh -yh/(zh*zh)]
The Jacobian of the homogenous coordinates with respect to dH is
[x0 x1 1 0 0 0 0 0 0]
[ 0 0 0 x0 x1 1 0 0 0]
[ 0 0 0 0 0 0 x0 x1 1]
The output Jacobian is minus their product, i.e.
[-x0/zh -x1/zh -1/zh 0 0 0 x0*xh/(zh*zh) x1*xh/(zh*zh) xh/(zh*zh)]
[ 0 0 0 -x0/zh -x1/zh -1/zh x0*yh/(zh*zh) x1*yh/(zh*zh) yh/(zh*zh)]*/
/*Compute warped point, which is the same as
homogenous coordinates of reprojection*/
xh=H[0]*x[0]+H[1]*x[1]+H[2];
yh=H[3]*x[0]+H[4]*x[1]+H[5];
zh=H[6]*x[0]+H[7]*x[1]+H[8];
mult=1.0/((zh!=0.0)?zh:1.0);
/*Compute inhomogenous residual*/
f[0]=y[0]-xh*mult;
f[1]=y[1]-yh*mult;
/*Compute Jacobian*/
mult2=mult*mult;
xh_mult2=xh*mult2;
yh_mult2=yh*mult2;
Jf_dx[0]= -x[0]*mult;
Jf_dx[1]= -x[1]*mult;
Jf_dx[2]= -mult;
Jf_dx[3]=0;
Jf_dx[4]=0;
Jf_dx[5]=0;
Jf_dx[6]=x[0]*xh_mult2;
Jf_dx[7]=x[1]*xh_mult2;
Jf_dx[8]=xh_mult2;
Jf_dx[9]=0;
Jf_dx[10]=0;
Jf_dx[11]=0;
Jf_dx[12]=Jf_dx[0];
Jf_dx[13]=Jf_dx[1];
Jf_dx[14]=Jf_dx[2];
Jf_dx[15]=x[0]*yh_mult2;
Jf_dx[16]=x[1]*yh_mult2;
Jf_dx[17]=yh_mult2;
}
/*!
Compute robust residual vector f between image point y and homography Hx of
image point x. Also compute Jacobian of f with respect
to an update dH of H*/
inline void db_DerivativeCauchyInhomHomographyReprojection(double Jf_dx[18],double f[2],const double y[2],const double H[9],
const double x[2],double one_over_scale2)
{
double Jf_dx_loc[18],f_loc[2];
double J[4],J0,J1,J2,J3;
/*Compute reprojection Jacobian*/
db_DerivativeInhomHomographyError(Jf_dx_loc,f_loc,y,H,x);
/*Compute robustifier Jacobian*/
db_CauchyDerivative(J,f,f_loc,one_over_scale2);
/*Multiply the robustifier Jacobian with
the reprojection Jacobian*/
J0=J[0];J1=J[1];J2=J[2];J3=J[3];
Jf_dx[0]=J0*Jf_dx_loc[0];
Jf_dx[1]=J0*Jf_dx_loc[1];
Jf_dx[2]=J0*Jf_dx_loc[2];
Jf_dx[3]= J1*Jf_dx_loc[12];
Jf_dx[4]= J1*Jf_dx_loc[13];
Jf_dx[5]= J1*Jf_dx_loc[14];
Jf_dx[6]=J0*Jf_dx_loc[6]+J1*Jf_dx_loc[15];
Jf_dx[7]=J0*Jf_dx_loc[7]+J1*Jf_dx_loc[16];
Jf_dx[8]=J0*Jf_dx_loc[8]+J1*Jf_dx_loc[17];
Jf_dx[9]= J2*Jf_dx_loc[0];
Jf_dx[10]=J2*Jf_dx_loc[1];
Jf_dx[11]=J2*Jf_dx_loc[2];
Jf_dx[12]= J3*Jf_dx_loc[12];
Jf_dx[13]= J3*Jf_dx_loc[13];
Jf_dx[14]= J3*Jf_dx_loc[14];
Jf_dx[15]=J2*Jf_dx_loc[6]+J3*Jf_dx_loc[15];
Jf_dx[16]=J2*Jf_dx_loc[7]+J3*Jf_dx_loc[16];
Jf_dx[17]=J2*Jf_dx_loc[8]+J3*Jf_dx_loc[17];
}
/*!
Compute residual vector f between image point y and rotation of
image point x by R. Also compute Jacobian of f with respect
to an update dx of R*/
inline void db_DerivativeInhomRotationReprojection(double Jf_dx[6],double f[2],const double y[2],const double R[9],
const double x[2])
{
double xh,yh,zh,mult,mult2,xh_mult2,yh_mult2;
/*The Jacobian of the inhomogenous coordinates with respect to
the homogenous is
[1/zh 0 -xh/(zh*zh)]
[ 0 1/zh -yh/(zh*zh)]
The Jacobian at zero of the homogenous coordinates with respect to
[sin(phi) sin(ohm) sin(kap)] is
[-rx2 0 rx1 ]
[ 0 rx2 -rx0 ]
[ rx0 -rx1 0 ]
The output Jacobian is minus their product, i.e.
[1+xh*xh/(zh*zh) -xh*yh/(zh*zh) -yh/zh]
[xh*yh/(zh*zh) -1-yh*yh/(zh*zh) xh/zh]*/
/*Compute rotated point, which is the same as
homogenous coordinates of reprojection*/
xh=R[0]*x[0]+R[1]*x[1]+R[2];
yh=R[3]*x[0]+R[4]*x[1]+R[5];
zh=R[6]*x[0]+R[7]*x[1]+R[8];
mult=1.0/((zh!=0.0)?zh:1.0);
/*Compute inhomogenous residual*/
f[0]=y[0]-xh*mult;
f[1]=y[1]-yh*mult;
/*Compute Jacobian*/
mult2=mult*mult;
xh_mult2=xh*mult2;
yh_mult2=yh*mult2;
Jf_dx[0]= 1.0+xh*xh_mult2;
Jf_dx[1]= -yh*xh_mult2;
Jf_dx[2]= -yh*mult;
Jf_dx[3]= -Jf_dx[1];
Jf_dx[4]= -1-yh*yh_mult2;
Jf_dx[5]= xh*mult;
}
/*!
Compute robust residual vector f between image point y and rotation of
image point x by R. Also compute Jacobian of f with respect
to an update dx of R*/
inline void db_DerivativeCauchyInhomRotationReprojection(double Jf_dx[6],double f[2],const double y[2],const double R[9],
const double x[2],double one_over_scale2)
{
double Jf_dx_loc[6],f_loc[2];
double J[4],J0,J1,J2,J3;
/*Compute reprojection Jacobian*/
db_DerivativeInhomRotationReprojection(Jf_dx_loc,f_loc,y,R,x);
/*Compute robustifier Jacobian*/
db_CauchyDerivative(J,f,f_loc,one_over_scale2);
/*Multiply the robustifier Jacobian with
the reprojection Jacobian*/
J0=J[0];J1=J[1];J2=J[2];J3=J[3];
Jf_dx[0]=J0*Jf_dx_loc[0]+J1*Jf_dx_loc[3];
Jf_dx[1]=J0*Jf_dx_loc[1]+J1*Jf_dx_loc[4];
Jf_dx[2]=J0*Jf_dx_loc[2]+J1*Jf_dx_loc[5];
Jf_dx[3]=J2*Jf_dx_loc[0]+J3*Jf_dx_loc[3];
Jf_dx[4]=J2*Jf_dx_loc[1]+J3*Jf_dx_loc[4];
Jf_dx[5]=J2*Jf_dx_loc[2]+J3*Jf_dx_loc[5];
}
/*!
// remove the outliers whose projection error is larger than pre-defined
*/
inline int db_RemoveOutliers_Homography(const double H[9], double *x_i,double *xp_i, double *wp,double *im, double *im_p, double *im_r, double *im_raw,double *im_raw_p,int point_count,double scale, double thresh=DB_OUTLIER_THRESHOLD)
{
double temp_valueE, t2;
int c;
int k1=0;
int k2=0;
int k3=0;
int numinliers=0;
int ind1;
int ind2;
int ind3;
int isinlier;
// experimentally determined
t2=1.0/(thresh*thresh*thresh*thresh);
// count the inliers
for(c=0;c<point_count;c++)
{
ind1=c<<1;
ind2=c<<2;
ind3=3*c;
temp_valueE=db_SquaredInhomogenousHomographyError(im_p+ind3,H,im+ind3);
isinlier=((temp_valueE<=t2)?1:0);
// if it is inlier, then copy the 3d and 2d correspondences
if (isinlier)
{
numinliers++;
x_i[k1]=x_i[ind1];
x_i[k1+1]=x_i[ind1+1];
xp_i[k1]=xp_i[ind1];
xp_i[k1+1]=xp_i[ind1+1];
k1=k1+2;
// original normalized pixel coordinates
im[k3]=im[ind3];
im[k3+1]=im[ind3+1];
im[k3+2]=im[ind3+2];
im_r[k3]=im_r[ind3];
im_r[k3+1]=im_r[ind3+1];
im_r[k3+2]=im_r[ind3+2];
im_p[k3]=im_p[ind3];
im_p[k3+1]=im_p[ind3+1];
im_p[k3+2]=im_p[ind3+2];
// left and right raw pixel coordinates
im_raw[k3] = im_raw[ind3];
im_raw[k3+1] = im_raw[ind3+1];
im_raw[k3+2] = im_raw[ind3+2]; // the index
im_raw_p[k3] = im_raw_p[ind3];
im_raw_p[k3+1] = im_raw_p[ind3+1];
im_raw_p[k3+2] = im_raw_p[ind3+2]; // the index
k3=k3+3;
// 3D coordinates
wp[k2]=wp[ind2];
wp[k2+1]=wp[ind2+1];
wp[k2+2]=wp[ind2+2];
wp[k2+3]=wp[ind2+3];
k2=k2+4;
}
}
return numinliers;
}
/*\}*/
#endif /* DB_METRICS */