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+/*
+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
+ (3-clause BSD License)
+
+Copyright (C) 2016, OpenCV Foundation, 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:
+
+ * Redistributions of source code must retain the above copyright notice,
+ this list of conditions and the following disclaimer.
+
+ * Redistributions 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.
+
+ * Neither the names of the copyright holders nor the names of the contributors
+ may 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 copyright holders 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.
+*/
+
+/**
+ * @file pcaflow.hpp
+ * @author Vladislav Samsonov <vvladxx@gmail.com>
+ * @brief Implementation of the PCAFlow algorithm from the following paper:
+ * http://files.is.tue.mpg.de/black/papers/cvpr2015_pcaflow.pdf
+ *
+ * @cite Wulff:CVPR:2015
+ *
+ * There are some key differences which distinguish this algorithm from the original PCAFlow (see paper):
+ * - Discrete Cosine Transform basis is used instead of basis extracted with PCA.
+ * Reasoning: DCT basis has comparable performance and it doesn't require additional storage space.
+ * Also, this decision helps to avoid overloading the algorithm with a lot of external input.
+ * - Usage of built-in OpenCV feature tracking instead of libviso.
+*/
+
+#ifndef __OPENCV_OPTFLOW_PCAFLOW_HPP__
+#define __OPENCV_OPTFLOW_PCAFLOW_HPP__
+
+#include "opencv2/core.hpp"
+#include "opencv2/video.hpp"
+
+namespace cv
+{
+namespace optflow
+{
+
+//! @addtogroup optflow
+//! @{
+
+/** @brief
+ * This class can be used for imposing a learned prior on the resulting optical flow.
+ * Solution will be regularized according to this prior.
+ * You need to generate appropriate prior file with "learn_prior.py" script beforehand.
+ */
+class CV_EXPORTS_W PCAPrior
+{
+private:
+ Mat L1;
+ Mat L2;
+ Mat c1;
+ Mat c2;
+
+public:
+ PCAPrior( const char *pathToPrior );
+
+ int getPadding() const { return L1.size().height; }
+
+ int getBasisSize() const { return L1.size().width; }
+
+ void fillConstraints( float *A1, float *A2, float *b1, float *b2 ) const;
+};
+
+/** @brief PCAFlow algorithm.
+ */
+class CV_EXPORTS_W OpticalFlowPCAFlow : public DenseOpticalFlow
+{
+protected:
+ const Ptr<const PCAPrior> prior;
+ const Size basisSize;
+ const float sparseRate; // (0 .. 0.1)
+ const float retainedCornersFraction; // [0 .. 1]
+ const float occlusionsThreshold;
+ const float dampingFactor;
+ const float claheClip;
+ bool useOpenCL;
+
+public:
+ /** @brief Creates an instance of PCAFlow algorithm.
+ * @param _prior Learned prior or no prior (default). @see cv::optflow::PCAPrior
+ * @param _basisSize Number of basis vectors.
+ * @param _sparseRate Controls density of sparse matches.
+ * @param _retainedCornersFraction Retained corners fraction.
+ * @param _occlusionsThreshold Occlusion threshold.
+ * @param _dampingFactor Regularization term for solving least-squares. It is not related to the prior regularization.
+ * @param _claheClip Clip parameter for CLAHE.
+ */
+ OpticalFlowPCAFlow( Ptr<const PCAPrior> _prior = Ptr<const PCAPrior>(), const Size _basisSize = Size( 18, 14 ),
+ float _sparseRate = 0.024, float _retainedCornersFraction = 0.2,
+ float _occlusionsThreshold = 0.0003, float _dampingFactor = 0.00002, float _claheClip = 14 );
+
+ void calc( InputArray I0, InputArray I1, InputOutputArray flow );
+ void collectGarbage();
+
+private:
+ void findSparseFeatures( UMat &from, UMat &to, std::vector<Point2f> &features,
+ std::vector<Point2f> &predictedFeatures ) const;
+
+ void removeOcclusions( UMat &from, UMat &to, std::vector<Point2f> &features,
+ std::vector<Point2f> &predictedFeatures ) const;
+
+ void getSystem( OutputArray AOut, OutputArray b1Out, OutputArray b2Out, const std::vector<Point2f> &features,
+ const std::vector<Point2f> &predictedFeatures, const Size size );
+
+ void getSystem( OutputArray A1Out, OutputArray A2Out, OutputArray b1Out, OutputArray b2Out,
+ const std::vector<Point2f> &features, const std::vector<Point2f> &predictedFeatures,
+ const Size size );
+
+ OpticalFlowPCAFlow& operator=( const OpticalFlowPCAFlow& ); // make it non-assignable
+};
+
+/** @brief Creates an instance of PCAFlow
+*/
+CV_EXPORTS_W Ptr<DenseOpticalFlow> createOptFlow_PCAFlow();
+
+//! @}
+
+}
+}
+
+#endif