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133 lines
4.9 KiB
133 lines
4.9 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) 2014, OpenCV Foundation, all rights reserved. |
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// Third party copyrights are property of their respective owners. |
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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_SALIENCY_BASE_CLASSES_HPP__ |
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#define __OPENCV_SALIENCY_BASE_CLASSES_HPP__ |
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#include "opencv2/core.hpp" |
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#include <opencv2/core/persistence.hpp> |
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#include "opencv2/imgproc.hpp" |
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#include <iostream> |
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#include <sstream> |
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#include <complex> |
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namespace cv |
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{ |
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namespace saliency |
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{ |
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//! @addtogroup saliency |
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//! @{ |
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/************************************ Saliency Base Class ************************************/ |
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class CV_EXPORTS_W Saliency : public virtual Algorithm |
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{ |
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public: |
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/** |
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* \brief Destructor |
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*/ |
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virtual ~Saliency(); |
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/** |
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* \brief Compute the saliency |
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* \param image The image. |
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* \param saliencyMap The computed saliency map. |
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* \return true if the saliency map is computed, false otherwise |
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*/ |
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CV_WRAP bool computeSaliency( InputArray image, OutputArray saliencyMap ); |
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protected: |
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virtual bool computeSaliencyImpl( InputArray image, OutputArray saliencyMap ) = 0; |
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String className; |
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}; |
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/************************************ Static Saliency Base Class ************************************/ |
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class CV_EXPORTS_W StaticSaliency : public virtual Saliency |
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{ |
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public: |
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/** @brief This function perform a binary map of given saliency map. This is obtained in this |
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way: |
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In a first step, to improve the definition of interest areas and facilitate identification of |
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targets, a segmentation by clustering is performed, using *K-means algorithm*. Then, to gain a |
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binary representation of clustered saliency map, since values of the map can vary according to |
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the characteristics of frame under analysis, it is not convenient to use a fixed threshold. So, |
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*Otsu's algorithm* is used, which assumes that the image to be thresholded contains two classes |
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of pixels or bi-modal histograms (e.g. foreground and back-ground pixels); later on, the |
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algorithm calculates the optimal threshold separating those two classes, so that their |
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intra-class variance is minimal. |
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@param _saliencyMap the saliency map obtained through one of the specialized algorithms |
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@param _binaryMap the binary map |
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*/ |
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CV_WRAP bool computeBinaryMap( InputArray _saliencyMap, OutputArray _binaryMap ); |
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protected: |
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virtual bool computeSaliencyImpl( InputArray image, OutputArray saliencyMap ) CV_OVERRIDE = 0; |
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}; |
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/************************************ Motion Saliency Base Class ************************************/ |
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class CV_EXPORTS_W MotionSaliency : public virtual Saliency |
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{ |
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protected: |
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virtual bool computeSaliencyImpl( InputArray image, OutputArray saliencyMap ) CV_OVERRIDE = 0; |
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}; |
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/************************************ Objectness Base Class ************************************/ |
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class CV_EXPORTS_W Objectness : public virtual Saliency |
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{ |
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protected: |
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virtual bool computeSaliencyImpl( InputArray image, OutputArray saliencyMap ) CV_OVERRIDE = 0; |
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}; |
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//! @} |
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} /* namespace saliency */ |
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} /* namespace cv */ |
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#endif
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