Commit 4b1d0c21 authored by jaco's avatar jaco

core implementation start

parent b07272f9
...@@ -99,6 +99,12 @@ class CV_EXPORTS_W MotionSaliencyBinWangApr2014 : public MotionSaliency ...@@ -99,6 +99,12 @@ class CV_EXPORTS_W MotionSaliencyBinWangApr2014 : public MotionSaliency
MotionSaliencyBinWangApr2014(); MotionSaliencyBinWangApr2014();
~MotionSaliencyBinWangApr2014(); ~MotionSaliencyBinWangApr2014();
typedef Ptr<Size> (Algorithm::*SizeGetter)();
typedef void (Algorithm::*SizeSetter)( const Ptr<Size> & );
Ptr<Size> getWsize();
void setWsize( const Ptr<Size> &newSize );
protected: protected:
bool computeSaliencyImpl( const InputArray image, OutputArray saliencyMap ); bool computeSaliencyImpl( const InputArray image, OutputArray saliencyMap );
AlgorithmInfo* info() const; AlgorithmInfo* info() const;
...@@ -112,13 +118,11 @@ class CV_EXPORTS_W MotionSaliencyBinWangApr2014 : public MotionSaliency ...@@ -112,13 +118,11 @@ class CV_EXPORTS_W MotionSaliencyBinWangApr2014 : public MotionSaliency
// Background model maintenance functions // Background model maintenance functions
bool templateOrdering(); bool templateOrdering();
bool templateReplacement(Mat finalBFMask); bool templateReplacement( Mat finalBFMask );
// Decision threshold adaptation and Activity control function // Decision threshold adaptation and Activity control function
bool activityControl(vector<Mat> noisePixelMask); //bool activityControl(vector<Mat> noisePixelMask);
bool decisionThresholdAdaptation(); //bool decisionThresholdAdaptation();
// changing structure // changing structure
vector<Mat> backgroundModel; // The vector represents the background template T0---TK of reference paper. vector<Mat> backgroundModel; // The vector represents the background template T0---TK of reference paper.
...@@ -129,14 +133,16 @@ class CV_EXPORTS_W MotionSaliencyBinWangApr2014 : public MotionSaliency ...@@ -129,14 +133,16 @@ class CV_EXPORTS_W MotionSaliencyBinWangApr2014 : public MotionSaliency
Mat epslonPixelsValue; // epslon threshold Mat epslonPixelsValue; // epslon threshold
//Mat activityPixelsValue; // Activity level of each pixel //Mat activityPixelsValue; // Activity level of each pixel
//vector<Mat> noisePixelMask; // We define a ‘noise-pixel’ as a pixel that has been classified as a foreground pixel during the full resolution //vector<Mat> noisePixelMask; // We define a ‘noise-pixel’ as a pixel that has been classified as a foreground pixel during the full resolution
// detection process,however, after the low resolution detection, it has become a // detection process,however, after the low resolution detection, it has become a
// background pixel. In a noise-pixel mask, the identified noise-pixels are set to 1 while other pixels are 0; // background pixel. In a noise-pixel mask, the identified noise-pixels are set to 1 while other pixels are 0;
//fixed parameter //fixed parameter
Ptr<Size> imgSize; // Size of input image
int K; // Number of background model template int K; // Number of background model template
float alpha; // Learning rate float alpha; // Learning rate
int L0, L1; // Upper-bound values for C0 and C1 (efficacy of the first two template (matrices) of backgroundModel int L0, L1; // Upper-bound values for C0 and C1 (efficacy of the first two template (matrices) of backgroundModel
int thetaL; // T0, T1 swap threshold int thetaL; // T0, T1 swap threshold
int thetaA; // Potential background value threshold
int gamma; // Parameter that controls the time that the newly updated long-term background value will remain in the int gamma; // Parameter that controls the time that the newly updated long-term background value will remain in the
// long-term template, regardless of any subsequent background changes. A relatively large (eg gamma=3) will // long-term template, regardless of any subsequent background changes. A relatively large (eg gamma=3) will
//restrain the generation of ghosts. //restrain the generation of ghosts.
......
/*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) 2013, 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*/
#include "precomp.hpp"
namespace cv
{
cv::Ptr<Size> MotionSaliencyBinWangApr2014::getWsize()
{
return imgSize;
}
void MotionSaliencyBinWangApr2014::setWsize( const cv::Ptr<Size>& newSize )
{
imgSize = newSize;
}
MotionSaliencyBinWangApr2014::MotionSaliencyBinWangApr2014()
{
epslonPixelsValue = Mat::zeros( imgSize->height, imgSize->width, CV_8U );
potentialBackground = Mat::zeros( imgSize->height, imgSize->width, CV_32FC2 );
backgroundModel=std::vector<Mat>( 4, Mat::zeros( imgSize->height, imgSize->width, CV_32FC2 ) );
K = 3; // Number of background model template
alpha = 0.01; // Learning rate
L0 = 6000; // Upper-bound values for C0 (efficacy of the first template (matrices) of backgroundModel
L1 = 4000; // Upper-bound values for C1 (efficacy of the second template (matrices) of backgroundModel
thetaL = 2500; // T0, T1 swap threshold
thetaA = 200;
gamma = 3;
className = "BinWangApr2014";
}
MotionSaliencyBinWangApr2014::~MotionSaliencyBinWangApr2014()
{
}
// classification (and adaptation) functions
bool MotionSaliencyBinWangApr2014::fullResolutionDetection( Mat image, Mat highResBFMask )
{
return true;
}
bool MotionSaliencyBinWangApr2014::lowResolutionDetection( Mat image, Mat lowResBFMask )
{
return true;
}
bool MotionSaliencyBinWangApr2014::templateUpdate( Mat highResBFMask )
{
return true;
}
// Background model maintenance functions
bool MotionSaliencyBinWangApr2014::templateOrdering()
{
return true;
}
bool MotionSaliencyBinWangApr2014::templateReplacement( Mat finalBFMask )
{
return true;
}
bool MotionSaliencyBinWangApr2014::computeSaliencyImpl( const InputArray image, OutputArray saliencyMap )
{
return true;
}
} // namespace cv
...@@ -52,7 +52,12 @@ CV_INIT_ALGORITHM( ...@@ -52,7 +52,12 @@ CV_INIT_ALGORITHM(
reinterpret_cast<SizeGetter>( &StaticSaliencySpectralResidual::getWsize ), reinterpret_cast<SizeGetter>( &StaticSaliencySpectralResidual::getWsize ),
reinterpret_cast<SizeSetter>( &StaticSaliencySpectralResidual::setWsize ) ) ); reinterpret_cast<SizeSetter>( &StaticSaliencySpectralResidual::setWsize ) ) );
//CV_INIT_ALGORITHM( MotionSaliencySuBSENSE, "SALIENCY.SuBSENSE", ); CV_INIT_ALGORITHM(
MotionSaliencyBinWangApr2014,
"SALIENCY.BinWangApr2014",
obj.info()->addParam( obj, "imgSize", obj.imgSize, false,
reinterpret_cast<SizeGetter>( &MotionSaliencyBinWangApr2014::getWsize ),
reinterpret_cast<SizeSetter>( &MotionSaliencyBinWangApr2014::setWsize ) ) );
CV_INIT_ALGORITHM( CV_INIT_ALGORITHM(
ObjectnessBING, "SALIENCY.BING", ObjectnessBING, "SALIENCY.BING",
...@@ -62,7 +67,7 @@ bool initModule_saliency( void ) ...@@ -62,7 +67,7 @@ bool initModule_saliency( void )
{ {
bool all = true; bool all = true;
all &= !StaticSaliencySpectralResidual_info_auto.name().empty(); all &= !StaticSaliencySpectralResidual_info_auto.name().empty();
//all &= !MotionSaliencySuBSENSE_info_auto.name().empty(); all &= !MotionSaliencyBinWangApr2014_info_auto.name().empty();
all &= !ObjectnessBING_info_auto.name().empty(); all &= !ObjectnessBING_info_auto.name().empty();
return all; return all;
......
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment