mirror of
https://github.com/opencv/opencv.git
synced 2024-11-30 06:10:02 +08:00
118 lines
4.6 KiB
C++
118 lines
4.6 KiB
C++
/*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.
|
|
//
|
|
//
|
|
// License Agreement
|
|
// For Open Source Computer Vision Library
|
|
//
|
|
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
|
|
// Copyright (C) 2009, Willow Garage Inc., 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 the copyright holders 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 "autocalib.hpp"
|
|
#include "util.hpp"
|
|
|
|
using namespace std;
|
|
using namespace cv;
|
|
|
|
void focalsFromHomography(const Mat& H, double &f0, double &f1, bool &f0_ok, bool &f1_ok)
|
|
{
|
|
CV_Assert(H.type() == CV_64F && H.size() == Size(3, 3));
|
|
|
|
const double* h = reinterpret_cast<const double*>(H.data);
|
|
|
|
double d1, d2; // Denominators
|
|
double v1, v2; // Focal squares value candidates
|
|
|
|
f1_ok = true;
|
|
d1 = h[6] * h[7];
|
|
d2 = (h[7] - h[6]) * (h[7] + h[6]);
|
|
v1 = -(h[0] * h[1] + h[3] * h[4]) / d1;
|
|
v2 = (h[0] * h[0] + h[3] * h[3] - h[1] * h[1] - h[4] * h[4]) / d2;
|
|
if (v1 < v2) swap(v1, v2);
|
|
if (v1 > 0 && v2 > 0) f1 = sqrt(abs(d1) > abs(d2) ? v1 : v2);
|
|
else if (v1 > 0) f1 = sqrt(v1);
|
|
else f1_ok = false;
|
|
|
|
f0_ok = true;
|
|
d1 = h[0] * h[3] + h[1] * h[4];
|
|
d2 = h[0] * h[0] + h[1] * h[1] - h[3] * h[3] - h[4] * h[4];
|
|
v1 = -h[2] * h[5] / d1;
|
|
v2 = (h[5] * h[5] - h[2] * h[2]) / d2;
|
|
if (v1 < v2) swap(v1, v2);
|
|
if (v1 > 0 && v2 > 0) f0 = sqrt(abs(d1) > abs(d2) ? v1 : v2);
|
|
else if (v1 > 0) f0 = sqrt(v1);
|
|
else f0_ok = false;
|
|
}
|
|
|
|
|
|
void estimateFocal(const vector<ImageFeatures> &features, const vector<MatchesInfo> &pairwise_matches,
|
|
vector<double> &focals)
|
|
{
|
|
const int num_images = static_cast<int>(features.size());
|
|
focals.resize(num_images);
|
|
|
|
vector<double> all_focals;
|
|
|
|
for (int i = 0; i < num_images; ++i)
|
|
{
|
|
for (int j = 0; j < num_images; ++j)
|
|
{
|
|
const MatchesInfo &m = pairwise_matches[i*num_images + j];
|
|
if (m.H.empty())
|
|
continue;
|
|
double f0, f1;
|
|
bool f0ok, f1ok;
|
|
focalsFromHomography(m.H, f0, f1, f0ok, f1ok);
|
|
if (f0ok && f1ok)
|
|
all_focals.push_back(sqrt(f0 * f1));
|
|
}
|
|
}
|
|
|
|
if (static_cast<int>(all_focals.size()) >= num_images - 1)
|
|
{
|
|
nth_element(all_focals.begin(), all_focals.begin() + all_focals.size()/2, all_focals.end());
|
|
for (int i = 0; i < num_images; ++i)
|
|
focals[i] = all_focals[all_focals.size()/2];
|
|
}
|
|
else
|
|
{
|
|
LOGLN("Can't estimate focal length, will use naive approach");
|
|
double focals_sum = 0;
|
|
for (int i = 0; i < num_images; ++i)
|
|
focals_sum += features[i].img_size.width + features[i].img_size.height;
|
|
for (int i = 0; i < num_images; ++i)
|
|
focals[i] = focals_sum / num_images;
|
|
}
|
|
}
|