mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
636 lines
17 KiB
636 lines
17 KiB
/*M/////////////////////////////////////////////////////////////////////////////////////// |
|
// |
|
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
|
// |
|
// By downloading, copying, installing or using the software you agree to this license. |
|
// If you do not agree to this license, do not download, install, |
|
// copy or use the software. |
|
// |
|
// |
|
// Intel License Agreement |
|
// For Open Source Computer Vision Library |
|
// |
|
// Copyright (C) 2000, Intel Corporation, all rights reserved. |
|
// Third party copyrights are property of their respective owners. |
|
// |
|
// Redistribution and use in source and binary forms, with or without modification, |
|
// are permitted provided that the following conditions are met: |
|
// |
|
// * Redistribution's of source code must retain the above copyright notice, |
|
// this list of conditions and the following disclaimer. |
|
// |
|
// * Redistribution's in binary form must reproduce the above copyright notice, |
|
// this list of conditions and the following disclaimer in the documentation |
|
// and/or other materials provided with the distribution. |
|
// |
|
// * The name of Intel Corporation may not be used to endorse or promote products |
|
// derived from this software without specific prior written permission. |
|
// |
|
// This software is provided by the copyright holders and contributors "as is" and |
|
// any express or implied warranties, including, but not limited to, the implied |
|
// warranties of merchantability and fitness for a particular purpose are disclaimed. |
|
// In no event shall the Intel Corporation or contributors be liable for any direct, |
|
// indirect, incidental, special, exemplary, or consequential damages |
|
// (including, but not limited to, procurement of substitute goods or services; |
|
// loss of use, data, or profits; or business interruption) however caused |
|
// and on any theory of liability, whether in contract, strict liability, |
|
// or tort (including negligence or otherwise) arising in any way out of |
|
// the use of this software, even if advised of the possibility of such damage. |
|
// |
|
//M*/ |
|
#include "precomp.hpp" |
|
|
|
namespace cv |
|
{ |
|
|
|
static const double eps = 1e-6; |
|
|
|
static void fitLine2D_wods( const Point2f* points, int count, float *weights, float *line ) |
|
{ |
|
double x = 0, y = 0, x2 = 0, y2 = 0, xy = 0, w = 0; |
|
double dx2, dy2, dxy; |
|
int i; |
|
float t; |
|
|
|
// Calculating the average of x and y... |
|
if( weights == 0 ) |
|
{ |
|
for( i = 0; i < count; i += 1 ) |
|
{ |
|
x += points[i].x; |
|
y += points[i].y; |
|
x2 += points[i].x * points[i].x; |
|
y2 += points[i].y * points[i].y; |
|
xy += points[i].x * points[i].y; |
|
} |
|
w = (float) count; |
|
} |
|
else |
|
{ |
|
for( i = 0; i < count; i += 1 ) |
|
{ |
|
x += weights[i] * points[i].x; |
|
y += weights[i] * points[i].y; |
|
x2 += weights[i] * points[i].x * points[i].x; |
|
y2 += weights[i] * points[i].y * points[i].y; |
|
xy += weights[i] * points[i].x * points[i].y; |
|
w += weights[i]; |
|
} |
|
} |
|
|
|
x /= w; |
|
y /= w; |
|
x2 /= w; |
|
y2 /= w; |
|
xy /= w; |
|
|
|
dx2 = x2 - x * x; |
|
dy2 = y2 - y * y; |
|
dxy = xy - x * y; |
|
|
|
t = (float) atan2( 2 * dxy, dx2 - dy2 ) / 2; |
|
line[0] = (float) cos( t ); |
|
line[1] = (float) sin( t ); |
|
|
|
line[2] = (float) x; |
|
line[3] = (float) y; |
|
} |
|
|
|
static void fitLine3D_wods( const Point3f * points, int count, float *weights, float *line ) |
|
{ |
|
int i; |
|
float w0 = 0; |
|
float x0 = 0, y0 = 0, z0 = 0; |
|
float x2 = 0, y2 = 0, z2 = 0, xy = 0, yz = 0, xz = 0; |
|
float dx2, dy2, dz2, dxy, dxz, dyz; |
|
float *v; |
|
float n; |
|
float det[9], evc[9], evl[3]; |
|
|
|
memset( evl, 0, 3*sizeof(evl[0])); |
|
memset( evc, 0, 9*sizeof(evl[0])); |
|
|
|
if( weights ) |
|
{ |
|
for( i = 0; i < count; i++ ) |
|
{ |
|
float x = points[i].x; |
|
float y = points[i].y; |
|
float z = points[i].z; |
|
float w = weights[i]; |
|
|
|
|
|
x2 += x * x * w; |
|
xy += x * y * w; |
|
xz += x * z * w; |
|
y2 += y * y * w; |
|
yz += y * z * w; |
|
z2 += z * z * w; |
|
x0 += x * w; |
|
y0 += y * w; |
|
z0 += z * w; |
|
w0 += w; |
|
} |
|
} |
|
else |
|
{ |
|
for( i = 0; i < count; i++ ) |
|
{ |
|
float x = points[i].x; |
|
float y = points[i].y; |
|
float z = points[i].z; |
|
|
|
x2 += x * x; |
|
xy += x * y; |
|
xz += x * z; |
|
y2 += y * y; |
|
yz += y * z; |
|
z2 += z * z; |
|
x0 += x; |
|
y0 += y; |
|
z0 += z; |
|
} |
|
w0 = (float) count; |
|
} |
|
|
|
x2 /= w0; |
|
xy /= w0; |
|
xz /= w0; |
|
y2 /= w0; |
|
yz /= w0; |
|
z2 /= w0; |
|
|
|
x0 /= w0; |
|
y0 /= w0; |
|
z0 /= w0; |
|
|
|
dx2 = x2 - x0 * x0; |
|
dxy = xy - x0 * y0; |
|
dxz = xz - x0 * z0; |
|
dy2 = y2 - y0 * y0; |
|
dyz = yz - y0 * z0; |
|
dz2 = z2 - z0 * z0; |
|
|
|
det[0] = dz2 + dy2; |
|
det[1] = -dxy; |
|
det[2] = -dxz; |
|
det[3] = det[1]; |
|
det[4] = dx2 + dz2; |
|
det[5] = -dyz; |
|
det[6] = det[2]; |
|
det[7] = det[5]; |
|
det[8] = dy2 + dx2; |
|
|
|
// Searching for a eigenvector of det corresponding to the minimal eigenvalue |
|
Mat _det( 3, 3, CV_32F, det ); |
|
Mat _evc( 3, 3, CV_32F, evc ); |
|
Mat _evl( 3, 1, CV_32F, evl ); |
|
eigen( _det, _evl, _evc ); |
|
i = evl[0] < evl[1] ? (evl[0] < evl[2] ? 0 : 2) : (evl[1] < evl[2] ? 1 : 2); |
|
|
|
v = &evc[i * 3]; |
|
n = (float) std::sqrt( (double)v[0] * v[0] + (double)v[1] * v[1] + (double)v[2] * v[2] ); |
|
n = (float)MAX(n, eps); |
|
line[0] = v[0] / n; |
|
line[1] = v[1] / n; |
|
line[2] = v[2] / n; |
|
line[3] = x0; |
|
line[4] = y0; |
|
line[5] = z0; |
|
} |
|
|
|
static double calcDist2D( const Point2f* points, int count, float *_line, float *dist ) |
|
{ |
|
int j; |
|
float px = _line[2], py = _line[3]; |
|
float nx = _line[1], ny = -_line[0]; |
|
double sum_dist = 0.; |
|
|
|
for( j = 0; j < count; j++ ) |
|
{ |
|
float x, y; |
|
|
|
x = points[j].x - px; |
|
y = points[j].y - py; |
|
|
|
dist[j] = (float) fabs( nx * x + ny * y ); |
|
sum_dist += dist[j]; |
|
} |
|
|
|
return sum_dist; |
|
} |
|
|
|
static double calcDist3D( const Point3f* points, int count, float *_line, float *dist ) |
|
{ |
|
int j; |
|
float px = _line[3], py = _line[4], pz = _line[5]; |
|
float vx = _line[0], vy = _line[1], vz = _line[2]; |
|
double sum_dist = 0.; |
|
|
|
for( j = 0; j < count; j++ ) |
|
{ |
|
float x, y, z; |
|
double p1, p2, p3; |
|
|
|
x = points[j].x - px; |
|
y = points[j].y - py; |
|
z = points[j].z - pz; |
|
|
|
p1 = vy * z - vz * y; |
|
p2 = vz * x - vx * z; |
|
p3 = vx * y - vy * x; |
|
|
|
dist[j] = (float) std::sqrt( p1*p1 + p2*p2 + p3*p3 ); |
|
sum_dist += dist[j]; |
|
} |
|
|
|
return sum_dist; |
|
} |
|
|
|
static void weightL1( float *d, int count, float *w ) |
|
{ |
|
int i; |
|
|
|
for( i = 0; i < count; i++ ) |
|
{ |
|
double t = fabs( (double) d[i] ); |
|
w[i] = (float)(1. / MAX(t, eps)); |
|
} |
|
} |
|
|
|
static void weightL12( float *d, int count, float *w ) |
|
{ |
|
int i; |
|
|
|
for( i = 0; i < count; i++ ) |
|
{ |
|
w[i] = 1.0f / (float) std::sqrt( 1 + (double) (d[i] * d[i] * 0.5) ); |
|
} |
|
} |
|
|
|
|
|
static void weightHuber( float *d, int count, float *w, float _c ) |
|
{ |
|
int i; |
|
const float c = _c <= 0 ? 1.345f : _c; |
|
|
|
for( i = 0; i < count; i++ ) |
|
{ |
|
if( d[i] < c ) |
|
w[i] = 1.0f; |
|
else |
|
w[i] = c/d[i]; |
|
} |
|
} |
|
|
|
|
|
static void weightFair( float *d, int count, float *w, float _c ) |
|
{ |
|
int i; |
|
const float c = _c == 0 ? 1 / 1.3998f : 1 / _c; |
|
|
|
for( i = 0; i < count; i++ ) |
|
{ |
|
w[i] = 1 / (1 + d[i] * c); |
|
} |
|
} |
|
|
|
static void weightWelsch( float *d, int count, float *w, float _c ) |
|
{ |
|
int i; |
|
const float c = _c == 0 ? 1 / 2.9846f : 1 / _c; |
|
|
|
for( i = 0; i < count; i++ ) |
|
{ |
|
w[i] = (float) std::exp( -d[i] * d[i] * c * c ); |
|
} |
|
} |
|
|
|
|
|
/* Takes an array of 2D points, type of distance (including user-defined |
|
distance specified by callbacks, fills the array of four floats with line |
|
parameters A, B, C, D, where (A, B) is the normalized direction vector, |
|
(C, D) is the point that belongs to the line. */ |
|
|
|
static void fitLine2D( const Point2f * points, int count, int dist, |
|
float _param, float reps, float aeps, float *line ) |
|
{ |
|
double EPS = count*FLT_EPSILON; |
|
void (*calc_weights) (float *, int, float *) = 0; |
|
void (*calc_weights_param) (float *, int, float *, float) = 0; |
|
int i, j, k; |
|
float _line[6], _lineprev[6]; |
|
float rdelta = reps != 0 ? reps : 1.0f; |
|
float adelta = aeps != 0 ? aeps : 0.01f; |
|
double min_err = DBL_MAX, err = 0; |
|
RNG rng((uint64)-1); |
|
|
|
memset( line, 0, 4*sizeof(line[0]) ); |
|
|
|
switch (dist) |
|
{ |
|
case CV_DIST_L2: |
|
return fitLine2D_wods( points, count, 0, line ); |
|
|
|
case CV_DIST_L1: |
|
calc_weights = weightL1; |
|
break; |
|
|
|
case CV_DIST_L12: |
|
calc_weights = weightL12; |
|
break; |
|
|
|
case CV_DIST_FAIR: |
|
calc_weights_param = weightFair; |
|
break; |
|
|
|
case CV_DIST_WELSCH: |
|
calc_weights_param = weightWelsch; |
|
break; |
|
|
|
case CV_DIST_HUBER: |
|
calc_weights_param = weightHuber; |
|
break; |
|
|
|
/*case DIST_USER: |
|
calc_weights = (void ( * )(float *, int, float *)) _PFP.fp; |
|
break;*/ |
|
default: |
|
CV_Error(CV_StsBadArg, "Unknown distance type"); |
|
} |
|
|
|
AutoBuffer<float> wr(count*2); |
|
float *w = wr, *r = w + count; |
|
|
|
for( k = 0; k < 20; k++ ) |
|
{ |
|
int first = 1; |
|
for( i = 0; i < count; i++ ) |
|
w[i] = 0.f; |
|
|
|
for( i = 0; i < MIN(count,10); ) |
|
{ |
|
j = rng.uniform(0, count); |
|
if( w[j] < FLT_EPSILON ) |
|
{ |
|
w[j] = 1.f; |
|
i++; |
|
} |
|
} |
|
|
|
fitLine2D_wods( points, count, w, _line ); |
|
for( i = 0; i < 30; i++ ) |
|
{ |
|
double sum_w = 0; |
|
|
|
if( first ) |
|
{ |
|
first = 0; |
|
} |
|
else |
|
{ |
|
double t = _line[0] * _lineprev[0] + _line[1] * _lineprev[1]; |
|
t = MAX(t,-1.); |
|
t = MIN(t,1.); |
|
if( fabs(acos(t)) < adelta ) |
|
{ |
|
float x, y, d; |
|
|
|
x = (float) fabs( _line[2] - _lineprev[2] ); |
|
y = (float) fabs( _line[3] - _lineprev[3] ); |
|
|
|
d = x > y ? x : y; |
|
if( d < rdelta ) |
|
break; |
|
} |
|
} |
|
/* calculate distances */ |
|
err = calcDist2D( points, count, _line, r ); |
|
if( err < EPS ) |
|
break; |
|
|
|
/* calculate weights */ |
|
if( calc_weights ) |
|
calc_weights( r, count, w ); |
|
else |
|
calc_weights_param( r, count, w, _param ); |
|
|
|
for( j = 0; j < count; j++ ) |
|
sum_w += w[j]; |
|
|
|
if( fabs(sum_w) > FLT_EPSILON ) |
|
{ |
|
sum_w = 1./sum_w; |
|
for( j = 0; j < count; j++ ) |
|
w[j] = (float)(w[j]*sum_w); |
|
} |
|
else |
|
{ |
|
for( j = 0; j < count; j++ ) |
|
w[j] = 1.f; |
|
} |
|
|
|
/* save the line parameters */ |
|
memcpy( _lineprev, _line, 4 * sizeof( float )); |
|
|
|
/* Run again... */ |
|
fitLine2D_wods( points, count, w, _line ); |
|
} |
|
|
|
if( err < min_err ) |
|
{ |
|
min_err = err; |
|
memcpy( line, _line, 4 * sizeof(line[0])); |
|
if( err < EPS ) |
|
break; |
|
} |
|
} |
|
} |
|
|
|
|
|
/* Takes an array of 3D points, type of distance (including user-defined |
|
distance specified by callbacks, fills the array of four floats with line |
|
parameters A, B, C, D, E, F, where (A, B, C) is the normalized direction vector, |
|
(D, E, F) is the point that belongs to the line. */ |
|
static void fitLine3D( Point3f * points, int count, int dist, |
|
float _param, float reps, float aeps, float *line ) |
|
{ |
|
double EPS = count*FLT_EPSILON; |
|
void (*calc_weights) (float *, int, float *) = 0; |
|
void (*calc_weights_param) (float *, int, float *, float) = 0; |
|
int i, j, k; |
|
float _line[6]={0,0,0,0,0,0}, _lineprev[6]={0,0,0,0,0,0}; |
|
float rdelta = reps != 0 ? reps : 1.0f; |
|
float adelta = aeps != 0 ? aeps : 0.01f; |
|
double min_err = DBL_MAX, err = 0; |
|
RNG rng((uint64)-1); |
|
|
|
switch (dist) |
|
{ |
|
case CV_DIST_L2: |
|
return fitLine3D_wods( points, count, 0, line ); |
|
|
|
case CV_DIST_L1: |
|
calc_weights = weightL1; |
|
break; |
|
|
|
case CV_DIST_L12: |
|
calc_weights = weightL12; |
|
break; |
|
|
|
case CV_DIST_FAIR: |
|
calc_weights_param = weightFair; |
|
break; |
|
|
|
case CV_DIST_WELSCH: |
|
calc_weights_param = weightWelsch; |
|
break; |
|
|
|
case CV_DIST_HUBER: |
|
calc_weights_param = weightHuber; |
|
break; |
|
|
|
default: |
|
CV_Error(CV_StsBadArg, "Unknown distance"); |
|
} |
|
|
|
AutoBuffer<float> buf(count*2); |
|
float *w = buf, *r = w + count; |
|
|
|
for( k = 0; k < 20; k++ ) |
|
{ |
|
int first = 1; |
|
for( i = 0; i < count; i++ ) |
|
w[i] = 0.f; |
|
|
|
for( i = 0; i < MIN(count,10); ) |
|
{ |
|
j = rng.uniform(0, count); |
|
if( w[j] < FLT_EPSILON ) |
|
{ |
|
w[j] = 1.f; |
|
i++; |
|
} |
|
} |
|
|
|
fitLine3D_wods( points, count, w, _line ); |
|
for( i = 0; i < 30; i++ ) |
|
{ |
|
double sum_w = 0; |
|
|
|
if( first ) |
|
{ |
|
first = 0; |
|
} |
|
else |
|
{ |
|
double t = _line[0] * _lineprev[0] + _line[1] * _lineprev[1] + _line[2] * _lineprev[2]; |
|
t = MAX(t,-1.); |
|
t = MIN(t,1.); |
|
if( fabs(acos(t)) < adelta ) |
|
{ |
|
float x, y, z, ax, ay, az, dx, dy, dz, d; |
|
|
|
x = _line[3] - _lineprev[3]; |
|
y = _line[4] - _lineprev[4]; |
|
z = _line[5] - _lineprev[5]; |
|
ax = _line[0] - _lineprev[0]; |
|
ay = _line[1] - _lineprev[1]; |
|
az = _line[2] - _lineprev[2]; |
|
dx = (float) fabs( y * az - z * ay ); |
|
dy = (float) fabs( z * ax - x * az ); |
|
dz = (float) fabs( x * ay - y * ax ); |
|
|
|
d = dx > dy ? (dx > dz ? dx : dz) : (dy > dz ? dy : dz); |
|
if( d < rdelta ) |
|
break; |
|
} |
|
} |
|
/* calculate distances */ |
|
err = calcDist3D( points, count, _line, r ); |
|
//if( err < FLT_EPSILON*count ) |
|
// break; |
|
|
|
/* calculate weights */ |
|
if( calc_weights ) |
|
calc_weights( r, count, w ); |
|
else |
|
calc_weights_param( r, count, w, _param ); |
|
|
|
for( j = 0; j < count; j++ ) |
|
sum_w += w[j]; |
|
|
|
if( fabs(sum_w) > FLT_EPSILON ) |
|
{ |
|
sum_w = 1./sum_w; |
|
for( j = 0; j < count; j++ ) |
|
w[j] = (float)(w[j]*sum_w); |
|
} |
|
else |
|
{ |
|
for( j = 0; j < count; j++ ) |
|
w[j] = 1.f; |
|
} |
|
|
|
/* save the line parameters */ |
|
memcpy( _lineprev, _line, 6 * sizeof( float )); |
|
|
|
/* Run again... */ |
|
fitLine3D_wods( points, count, w, _line ); |
|
} |
|
|
|
if( err < min_err ) |
|
{ |
|
min_err = err; |
|
memcpy( line, _line, 6 * sizeof(line[0])); |
|
if( err < EPS ) |
|
break; |
|
} |
|
} |
|
} |
|
|
|
} |
|
|
|
void cv::fitLine( InputArray _points, OutputArray _line, int distType, |
|
double param, double reps, double aeps ) |
|
{ |
|
Mat points = _points.getMat(); |
|
|
|
float linebuf[6]={0.f}; |
|
int npoints2 = points.checkVector(2, -1, false); |
|
int npoints3 = points.checkVector(3, -1, false); |
|
|
|
CV_Assert( npoints2 >= 0 || npoints3 >= 0 ); |
|
|
|
if( points.depth() != CV_32F || !points.isContinuous() ) |
|
{ |
|
Mat temp; |
|
points.convertTo(temp, CV_32F); |
|
points = temp; |
|
} |
|
|
|
if( npoints2 >= 0 ) |
|
fitLine2D( points.ptr<Point2f>(), npoints2, distType, |
|
(float)param, (float)reps, (float)aeps, linebuf); |
|
else |
|
fitLine3D( points.ptr<Point3f>(), npoints3, distType, |
|
(float)param, (float)reps, (float)aeps, linebuf); |
|
|
|
Mat(npoints2 >= 0 ? 4 : 6, 1, CV_32F, linebuf).copyTo(_line); |
|
} |
|
|
|
|
|
CV_IMPL void |
|
cvFitLine( const CvArr* array, int dist, double param, |
|
double reps, double aeps, float *line ) |
|
{ |
|
CV_Assert(line != 0); |
|
|
|
cv::AutoBuffer<double> buf; |
|
cv::Mat points = cv::cvarrToMat(array, false, false, 0, &buf); |
|
cv::Mat linemat(points.checkVector(2) >= 0 ? 4 : 6, 1, CV_32F, line); |
|
|
|
cv::fitLine(points, linemat, dist, param, reps, aeps); |
|
} |
|
|
|
/* End of file. */
|
|
|