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+/*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) 2015, Baisheng Lai (laibaisheng@gmail.com), Zhejiang University,
+// all rights reserved.
+//
+// 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*/
+
+#ifndef __OPENCV_RANDOMPATTERN_HPP__
+#define __OPENCV_RANDOMPATTERN_HPP__
+
+#include "opencv2/features2d.hpp"
+#include "opencv2/highgui.hpp"
+
+namespace cv { namespace randpattern {
+
+
+//! @addtogroup ccalib
+//! @{
+
+/** @brief Class for finding features points and corresponding 3D in world coordinate of
+a "random" pattern, which can be to be used in calibration. It is useful when pattern is
+partly occluded or only a part of pattern can be observed in multiple cameras calibration.
+The pattern can be generated by RandomPatternGenerator class described in this file.
+
+Please refer to paper
+    B. Li, L. Heng, K. Kevin  and M. Pollefeys, "A Multiple-Camera System
+    Calibration Toolbox Using A Feature Descriptor-Based Calibration
+    Pattern", in IROS 2013.
+*/
+
+class CV_EXPORTS RandomPatternCornerFinder
+{
+public:
+
+    /* @brief Construct RandomPatternCornerFinder object
+
+    @param patternWidth the real width of "random" pattern in a user defined unit.
+    @param patternHeight the real height of "random" pattern in a user defined unit.
+    @param nMiniMatch number of minimal matches, otherwise that image is abandoned
+    @depth depth of output objectPoints and imagePoints, set it to be CV_32F or CV_64F.
+    @showExtraction whether show feature extraction, 0 for no and 1 for yes.
+    @detector feature detector to detect feature points in pattern and images.
+    @descriptor feature descriptor.
+    @matcher feature matcher.
+    */
+    RandomPatternCornerFinder(float patternWidth, float patternHeight,
+        int nminiMatch = 20, int depth = CV_32F, int verbose = 0, int showExtraction = 0,
+        Ptr<FeatureDetector> detector = AKAZE::create(AKAZE::DESCRIPTOR_MLDB, 0, 3, 0.005f),
+        Ptr<DescriptorExtractor> descriptor = AKAZE::create(AKAZE::DESCRIPTOR_MLDB,0, 3, 0.005f),
+        Ptr<DescriptorMatcher> matcher = DescriptorMatcher::create("BruteForce-L1"));
+
+    /* @brief Load pattern image and compute features for pattern
+    @param patternImage image for "random" pattern generated by RandomPatternGenerator, run it first.
+    */
+    void loadPattern(cv::Mat patternImage);
+
+    /* @brief Compute matched object points and image points which are used for calibration
+    The objectPoints (3D) and imagePoints (2D) are stored inside the class. Run getObjectPoints()
+    and getImagePoints() to get them.
+
+    @param inputImages vector of 8-bit grayscale images containing "random" pattern
+    that are used for calibration.
+    */
+    void computeObjectImagePoints(std::vector<cv::Mat> inputImages);
+
+    //void computeObjectImagePoints2(std::vector<cv::Mat> inputImages);
+
+    /* @brief Compute object and image points for a single image. It returns a vector<Mat> that
+    the first element stores the imagePoints and the second one stores the objectPoints.
+
+    @param inputImage single input image for calibration
+    */
+    std::vector<cv::Mat> computeObjectImagePointsForSingle(cv::Mat inputImage);
+
+    /* @brief Get object(3D) points
+    */
+    std::vector<cv::Mat> getObjectPoints();
+
+    /* @brief and image(2D) points
+    */
+    std::vector<cv::Mat> getImagePoints();
+
+private:
+
+    std::vector<cv::Mat> _objectPonits, _imagePoints;
+    float _patternWidth, _patternHeight;
+    cv::Size _patternImageSize;
+    int _nminiMatch;
+    int _depth;
+	int _verbose;
+
+    Ptr<FeatureDetector> _detector;
+    Ptr<DescriptorExtractor> _descriptor;
+    Ptr<DescriptorMatcher> _matcher;
+    Mat _descriptorPattern;
+    std::vector<cv::KeyPoint> _keypointsPattern;
+    Mat _patternImage;
+    int _showExtraction;
+
+    void keyPoints2MatchedLocation(const std::vector<cv::KeyPoint>& imageKeypoints,
+        const std::vector<cv::KeyPoint>& patternKeypoints, const std::vector<cv::DMatch> matchces,
+        cv::Mat& matchedImagelocation, cv::Mat& matchedPatternLocation);
+    void getFilteredLocation(cv::Mat& imageKeypoints, cv::Mat& patternKeypoints, const cv::Mat mask);
+    void getObjectImagePoints(const cv::Mat& imageKeypoints, const cv::Mat& patternKeypoints);
+    void crossCheckMatching( cv::Ptr<DescriptorMatcher>& descriptorMatcher,
+        const Mat& descriptors1, const Mat& descriptors2,
+        std::vector<DMatch>& filteredMatches12, int knn=1 );
+    void drawCorrespondence(const Mat& image1, const std::vector<cv::KeyPoint> keypoint1,
+        const Mat& image2, const std::vector<cv::KeyPoint> keypoint2, const std::vector<cv::DMatch> matchces,
+        const Mat& mask1, const Mat& mask2, const int step);
+};
+
+/* @brief Class to generate "random" pattern image that are used for RandomPatternCornerFinder
+Please refer to paper
+B. Li, L. Heng, K. Kevin  and M. Pollefeys, "A Multiple-Camera System
+Calibration Toolbox Using A Feature Descriptor-Based Calibration
+Pattern", in IROS 2013.
+*/
+class CV_EXPORTS RandomPatternGenerator
+{
+public:
+    /* @brief Construct RandomPatternGenerator
+
+    @param imageWidth image width of the generated pattern image
+    @param imageHeight image height of the generated pattern image
+    */
+    RandomPatternGenerator(int imageWidth, int imageHeight);
+
+    /* @brief Generate pattern
+    */
+    void generatePattern();
+    /* @brief Get pattern
+    */
+    cv::Mat getPattern();
+private:
+    cv::Mat _pattern;
+    int _imageWidth, _imageHeight;
+};
+
+//! @}
+
+}} //namespace randpattern, cv
+#endif
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