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212 lines
8.3 KiB
212 lines
8.3 KiB
/*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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// License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2015, Baisheng Lai (laibaisheng@gmail.com), Zhejiang University, |
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// all rights reserved. |
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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 the copyright holders 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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#ifndef __OPENCV_MULTICAMERACALIBRATION_HPP__ |
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#define __OPENCV_MULTICAMERACALIBRATION_HPP__ |
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#include "opencv2/ccalib/randpattern.hpp" |
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#include "opencv2/ccalib/omnidir.hpp" |
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#include <string> |
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#include <iostream> |
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namespace cv { namespace multicalib { |
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//! @addtogroup ccalib |
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//! @{ |
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#define HEAD -1 |
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#define INVALID -2 |
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/** @brief Class for multiple camera calibration that supports pinhole camera and omnidirection camera. |
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For omnidirectional camera model, please refer to omnidir.hpp in ccalib module. |
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It first calibrate each camera individually, then a bundle adjustment like optimization is applied to |
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refine extrinsic parameters. So far, it only support "random" pattern for calibration, |
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see randomPattern.hpp in ccalib module for details. |
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Images that are used should be named by "cameraIdx-timestamp.*", several images with the same timestamp |
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means that they are the same pattern that are photographed. cameraIdx should start from 0. |
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For more details, please refer to paper |
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B. Li, L. Heng, K. Kevin and M. Pollefeys, "A Multiple-Camera System |
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Calibration Toolbox Using A Feature Descriptor-Based Calibration |
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Pattern", in IROS 2013. |
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*/ |
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class CV_EXPORTS MultiCameraCalibration |
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{ |
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public: |
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enum { |
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PINHOLE, |
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OMNIDIRECTIONAL |
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//FISHEYE |
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}; |
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// an edge connects a camera and pattern |
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struct edge |
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{ |
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int cameraVertex; // vertex index for camera in this edge |
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int photoVertex; // vertex index for pattern in this edge |
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int photoIndex; // photo index among photos for this camera |
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Mat transform; // transform from pattern to camera |
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edge(int cv, int pv, int pi, Mat trans) |
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{ |
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cameraVertex = cv; |
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photoVertex = pv; |
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photoIndex = pi; |
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transform = trans; |
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} |
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}; |
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struct vertex |
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{ |
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Mat pose; // relative pose to the first camera. For camera vertex, it is the |
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// transform from the first camera to this camera, for pattern vertex, |
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// it is the transform from pattern to the first camera |
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int timestamp; // timestamp of photo, only available for photo vertex |
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vertex(Mat po, int ts) |
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{ |
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pose = po; |
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timestamp = ts; |
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} |
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vertex() |
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{ |
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pose = Mat::eye(4, 4, CV_32F); |
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timestamp = -1; |
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} |
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}; |
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/* @brief Constructor |
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@param cameraType camera type, PINHOLE or OMNIDIRECTIONAL |
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@param nCameras number of cameras |
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@fileName filename of string list that are used for calibration, the file is generated |
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by imagelist_creator from OpenCv samples. The first one in the list is the pattern filename. |
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@patternWidth the physical width of pattern, in user defined unit. |
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@patternHeight the physical height of pattern, in user defined unit. |
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@showExtration whether show extracted features and feature filtering. |
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@nMiniMatches minimal number of matched features for a frame. |
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@flags Calibration flags |
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@criteria optimization stopping criteria. |
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@detector feature detector that detect feature points in pattern and images. |
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@descriptor feature descriptor. |
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@matcher feature matcher. |
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*/ |
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MultiCameraCalibration(int cameraType, int nCameras, const std::string& fileName, float patternWidth, |
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float patternHeight, int verbose = 0, int showExtration = 0, int nMiniMatches = 20, int flags = 0, |
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TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 200, 1e-7), |
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Ptr<FeatureDetector> detector = AKAZE::create(AKAZE::DESCRIPTOR_MLDB, 0, 3, 0.006f), |
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Ptr<DescriptorExtractor> descriptor = AKAZE::create(AKAZE::DESCRIPTOR_MLDB,0, 3, 0.006f), |
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Ptr<DescriptorMatcher> matcher = DescriptorMatcher::create("BruteForce-L1")); |
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/* @brief load images |
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*/ |
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void loadImages(); |
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/* @brief initialize multiple camera calibration. It calibrates each camera individually. |
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*/ |
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void initialize(); |
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/* @brief optimization extrinsic parameters |
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*/ |
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double optimizeExtrinsics(); |
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/* @brief run multi-camera camera calibration, it runs loadImage(), initialize() and optimizeExtrinsics() |
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*/ |
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double run(); |
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/* @brief write camera parameters to file. |
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*/ |
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void writeParameters(const std::string& filename); |
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private: |
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std::vector<std::string> readStringList(); |
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int getPhotoVertex(int timestamp); |
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void graphTraverse(const Mat& G, int begin, std::vector<int>& order, std::vector<int>& pre); |
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void findRowNonZero(const Mat& row, Mat& idx); |
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void computeJacobianExtrinsic(const Mat& extrinsicParams, Mat& JTJ_inv, Mat& JTE); |
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void computePhotoCameraJacobian(const Mat& rvecPhoto, const Mat& tvecPhoto, const Mat& rvecCamera, |
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const Mat& tvecCamera, Mat& rvecTran, Mat& tvecTran, const Mat& objectPoints, const Mat& imagePoints, const Mat& K, |
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const Mat& distort, const Mat& xi, Mat& jacobianPhoto, Mat& jacobianCamera, Mat& E); |
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void compose_motion(InputArray _om1, InputArray _T1, InputArray _om2, InputArray _T2, Mat& om3, Mat& T3, Mat& dom3dom1, |
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Mat& dom3dT1, Mat& dom3dom2, Mat& dom3dT2, Mat& dT3dom1, Mat& dT3dT1, Mat& dT3dom2, Mat& dT3dT2); |
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void JRodriguesMatlab(const Mat& src, Mat& dst); |
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void dAB(InputArray A, InputArray B, OutputArray dABdA, OutputArray dABdB); |
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double computeProjectError(Mat& parameters); |
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void vector2parameters(const Mat& parameters, std::vector<Vec3f>& rvecVertex, std::vector<Vec3f>& tvecVertexs); |
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void parameters2vector(const std::vector<Vec3f>& rvecVertex, const std::vector<Vec3f>& tvecVertex, Mat& parameters); |
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int _camType; //PINHOLE, FISHEYE or OMNIDIRECTIONAL |
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int _nCamera; |
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int _nMiniMatches; |
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int _flags; |
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int _verbose; |
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double _error; |
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float _patternWidth, _patternHeight; |
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TermCriteria _criteria; |
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std::string _filename; |
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int _showExtraction; |
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Ptr<FeatureDetector> _detector; |
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Ptr<DescriptorExtractor> _descriptor; |
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Ptr<DescriptorMatcher> _matcher; |
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std::vector<edge> _edgeList; |
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std::vector<vertex> _vertexList; |
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std::vector<std::vector<cv::Mat> > _objectPointsForEachCamera; |
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std::vector<std::vector<cv::Mat> > _imagePointsForEachCamera; |
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std::vector<cv::Mat> _cameraMatrix; |
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std::vector<cv::Mat> _distortCoeffs; |
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std::vector<cv::Mat> _xi; |
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std::vector<std::vector<Mat> > _omEachCamera, _tEachCamera; |
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}; |
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//! @} |
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}} // namespace multicalib, cv |
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#endif |