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