1 /*M/////////////////////////////////////////////////////////////////////////////////////// 2 // 3 // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. 4 // 5 // By downloading, copying, installing or using the software you agree to this license. 6 // If you do not agree to this license, do not download, install, 7 // copy or use the software. 8 // 9 // 10 // License Agreement 11 // For Open Source Computer Vision Library 12 // 13 // Copyright (C) 2015, Baisheng Lai (laibaisheng@gmail.com), Zhejiang University, 14 // all rights reserved. 15 // 16 // Redistribution and use in source and binary forms, with or without modification, 17 // are permitted provided that the following conditions are met: 18 // 19 // * Redistribution's of source code must retain the above copyright notice, 20 // this list of conditions and the following disclaimer. 21 // 22 // * Redistribution's in binary form must reproduce the above copyright notice, 23 // this list of conditions and the following disclaimer in the documentation 24 // and/or other materials provided with the distribution. 25 // 26 // * The name of the copyright holders may not be used to endorse or promote products 27 // derived from this software without specific prior written permission. 28 // 29 // This software is provided by the copyright holders and contributors "as is" and 30 // any express or implied warranties, including, but not limited to, the implied 31 // warranties of merchantability and fitness for a particular purpose are disclaimed. 32 // In no event shall the Intel Corporation or contributors be liable for any direct, 33 // indirect, incidental, special, exemplary, or consequential damages 34 // (including, but not limited to, procurement of substitute goods or services; 35 // loss of use, data, or profits; or business interruption) however caused 36 // and on any theory of liability, whether in contract, strict liability, 37 // or tort (including negligence or otherwise) arising in any way out of 38 // the use of this software, even if advised of the possibility of such damage. 39 // 40 //M*/ 41 42 #ifndef __OPENCV_RANDOMPATTERN_HPP__ 43 #define __OPENCV_RANDOMPATTERN_HPP__ 44 45 #include "opencv2/features2d.hpp" 46 #include "opencv2/highgui.hpp" 47 48 namespace cv { namespace randpattern { 49 50 51 //! @addtogroup ccalib 52 //! @{ 53 54 /** @brief Class for finding features points and corresponding 3D in world coordinate of 55 a "random" pattern, which can be to be used in calibration. It is useful when pattern is 56 partly occluded or only a part of pattern can be observed in multiple cameras calibration. 57 The pattern can be generated by RandomPatternGenerator class described in this file. 58 59 Please refer to paper 60 B. Li, L. Heng, K. Kevin and M. Pollefeys, "A Multiple-Camera System 61 Calibration Toolbox Using A Feature Descriptor-Based Calibration 62 Pattern", in IROS 2013. 63 */ 64 65 class CV_EXPORTS RandomPatternCornerFinder 66 { 67 public: 68 69 /* @brief Construct RandomPatternCornerFinder object 70 71 @param patternWidth the real width of "random" pattern in a user defined unit. 72 @param patternHeight the real height of "random" pattern in a user defined unit. 73 @param nMiniMatch number of minimal matches, otherwise that image is abandoned 74 @depth depth of output objectPoints and imagePoints, set it to be CV_32F or CV_64F. 75 @showExtraction whether show feature extraction, 0 for no and 1 for yes. 76 @detector feature detector to detect feature points in pattern and images. 77 @descriptor feature descriptor. 78 @matcher feature matcher. 79 */ 80 RandomPatternCornerFinder(float patternWidth, float patternHeight, 81 int nminiMatch = 20, int depth = CV_32F, int verbose = 0, int showExtraction = 0, 82 Ptr<FeatureDetector> detector = AKAZE::create(AKAZE::DESCRIPTOR_MLDB, 0, 3, 0.005f), 83 Ptr<DescriptorExtractor> descriptor = AKAZE::create(AKAZE::DESCRIPTOR_MLDB,0, 3, 0.005f), 84 Ptr<DescriptorMatcher> matcher = DescriptorMatcher::create("BruteForce-L1")); 85 86 /* @brief Load pattern image and compute features for pattern 87 @param patternImage image for "random" pattern generated by RandomPatternGenerator, run it first. 88 */ 89 void loadPattern(const cv::Mat &patternImage); 90 91 /* @brief Load pattern and features 92 @param patternImage image for "random" pattern generated by RandomPatternGenerator, run it first. 93 @param patternKeyPoints keyPoints created from a FeatureDetector. 94 @param patternDescriptors descriptors created from a DescriptorExtractor. 95 */ 96 void loadPattern(const cv::Mat &patternImage, const std::vector<cv::KeyPoint> &patternKeyPoints, const cv::Mat &patternDescriptors); 97 98 /* @brief Compute matched object points and image points which are used for calibration 99 The objectPoints (3D) and imagePoints (2D) are stored inside the class. Run getObjectPoints() 100 and getImagePoints() to get them. 101 102 @param inputImages vector of 8-bit grayscale images containing "random" pattern 103 that are used for calibration. 104 */ 105 void computeObjectImagePoints(std::vector<cv::Mat> inputImages); 106 107 //void computeObjectImagePoints2(std::vector<cv::Mat> inputImages); 108 109 /* @brief Compute object and image points for a single image. It returns a vector<Mat> that 110 the first element stores the imagePoints and the second one stores the objectPoints. 111 112 @param inputImage single input image for calibration 113 */ 114 std::vector<cv::Mat> computeObjectImagePointsForSingle(cv::Mat inputImage); 115 116 /* @brief Get object(3D) points 117 */ 118 const std::vector<cv::Mat> &getObjectPoints(); 119 120 /* @brief and image(2D) points 121 */ 122 const std::vector<cv::Mat> &getImagePoints(); 123 124 private: 125 126 std::vector<cv::Mat> _objectPonits, _imagePoints; 127 float _patternWidth, _patternHeight; 128 cv::Size _patternImageSize; 129 int _nminiMatch; 130 int _depth; 131 int _verbose; 132 133 Ptr<FeatureDetector> _detector; 134 Ptr<DescriptorExtractor> _descriptor; 135 Ptr<DescriptorMatcher> _matcher; 136 Mat _descriptorPattern; 137 std::vector<cv::KeyPoint> _keypointsPattern; 138 Mat _patternImage; 139 int _showExtraction; 140 141 void keyPoints2MatchedLocation(const std::vector<cv::KeyPoint>& imageKeypoints, 142 const std::vector<cv::KeyPoint>& patternKeypoints, const std::vector<cv::DMatch> matchces, 143 cv::Mat& matchedImagelocation, cv::Mat& matchedPatternLocation); 144 void getFilteredLocation(cv::Mat& imageKeypoints, cv::Mat& patternKeypoints, const cv::Mat mask); 145 void getObjectImagePoints(const cv::Mat& imageKeypoints, const cv::Mat& patternKeypoints); 146 void crossCheckMatching( cv::Ptr<DescriptorMatcher>& descriptorMatcher, 147 const Mat& descriptors1, const Mat& descriptors2, 148 std::vector<DMatch>& filteredMatches12, int knn=1 ); 149 void drawCorrespondence(const Mat& image1, const std::vector<cv::KeyPoint> keypoint1, 150 const Mat& image2, const std::vector<cv::KeyPoint> keypoint2, const std::vector<cv::DMatch> matchces, 151 const Mat& mask1, const Mat& mask2, const int step); 152 }; 153 154 /* @brief Class to generate "random" pattern image that are used for RandomPatternCornerFinder 155 Please refer to paper 156 B. Li, L. Heng, K. Kevin and M. Pollefeys, "A Multiple-Camera System 157 Calibration Toolbox Using A Feature Descriptor-Based Calibration 158 Pattern", in IROS 2013. 159 */ 160 class CV_EXPORTS RandomPatternGenerator 161 { 162 public: 163 /* @brief Construct RandomPatternGenerator 164 165 @param imageWidth image width of the generated pattern image 166 @param imageHeight image height of the generated pattern image 167 */ 168 RandomPatternGenerator(int imageWidth, int imageHeight); 169 170 /* @brief Generate pattern 171 */ 172 void generatePattern(); 173 /* @brief Get pattern 174 */ 175 cv::Mat getPattern(); 176 private: 177 cv::Mat _pattern; 178 int _imageWidth, _imageHeight; 179 }; 180 181 //! @} 182 183 }} //namespace randpattern, cv 184 #endif