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Diffstat (limited to 'thirdparty/linux/include/opencv2/saliency/saliencyBaseClasses.hpp')
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diff --git a/thirdparty/linux/include/opencv2/saliency/saliencyBaseClasses.hpp b/thirdparty/linux/include/opencv2/saliency/saliencyBaseClasses.hpp new file mode 100644 index 0000000..65f9d07 --- /dev/null +++ b/thirdparty/linux/include/opencv2/saliency/saliencyBaseClasses.hpp @@ -0,0 +1,144 @@ +/*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) 2014, 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: + // + // * 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_SALIENCY_BASE_CLASSES_HPP__ +#define __OPENCV_SALIENCY_BASE_CLASSES_HPP__ + +#include "opencv2/core.hpp" +#include <opencv2/core/persistence.hpp> +#include "opencv2/imgproc.hpp" +#include <iostream> +#include <sstream> +#include <complex> + +namespace cv +{ +namespace saliency +{ + +//! @addtogroup saliency +//! @{ + +/************************************ Saliency Base Class ************************************/ + +class CV_EXPORTS_W Saliency : public virtual Algorithm +{ + public: + /** + * \brief Destructor + */ + virtual ~Saliency(); + + /** + * \brief Create Saliency by saliency type. + */ + static Ptr<Saliency> create( const String& saliencyType ); + + /** + * \brief Compute the saliency + * \param image The image. + * \param saliencyMap The computed saliency map. + * \return true if the saliency map is computed, false otherwise + */ + CV_WRAP bool computeSaliency( InputArray image, OutputArray saliencyMap ); + + /** + * \brief Get the name of the specific saliency type + * \return The name of the tracker initializer + */ + CV_WRAP String getClassName() const; + + protected: + + virtual bool computeSaliencyImpl( InputArray image, OutputArray saliencyMap ) = 0; + String className; +}; + +/************************************ Static Saliency Base Class ************************************/ +class CV_EXPORTS_W StaticSaliency : public virtual Saliency +{ + public: + + /** @brief This function perform a binary map of given saliency map. This is obtained in this + way: + + In a first step, to improve the definition of interest areas and facilitate identification of + targets, a segmentation by clustering is performed, using *K-means algorithm*. Then, to gain a + binary representation of clustered saliency map, since values of the map can vary according to + the characteristics of frame under analysis, it is not convenient to use a fixed threshold. So, + *Otsu’s algorithm* is used, which assumes that the image to be thresholded contains two classes + of pixels or bi-modal histograms (e.g. foreground and back-ground pixels); later on, the + algorithm calculates the optimal threshold separating those two classes, so that their + intra-class variance is minimal. + + @param _saliencyMap the saliency map obtained through one of the specialized algorithms + @param _binaryMap the binary map + */ + CV_WRAP bool computeBinaryMap( InputArray _saliencyMap, OutputArray _binaryMap ); + protected: + virtual bool computeSaliencyImpl( InputArray image, OutputArray saliencyMap )=0; + +}; + +/************************************ Motion Saliency Base Class ************************************/ +class CV_EXPORTS_W MotionSaliency : public virtual Saliency +{ + + protected: + virtual bool computeSaliencyImpl( InputArray image, OutputArray saliencyMap )=0; + +}; + +/************************************ Objectness Base Class ************************************/ +class CV_EXPORTS_W Objectness : public virtual Saliency +{ + + protected: + virtual bool computeSaliencyImpl( InputArray image, OutputArray saliencyMap )=0; + +}; + +//! @} + +} /* namespace saliency */ +} /* namespace cv */ + +#endif |