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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) 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 "trackerBoostingModel.hpp"
/**
* TrackerBoostingModel
*/
namespace cv
{
TrackerBoostingModel::TrackerBoostingModel( const Rect& boundingBox )
{
mode = MODE_POSITIVE;
Ptr<TrackerStateEstimatorAdaBoosting::TrackerAdaBoostingTargetState> initState =
Ptr<TrackerStateEstimatorAdaBoosting::TrackerAdaBoostingTargetState>(
new TrackerStateEstimatorAdaBoosting::TrackerAdaBoostingTargetState( Point2f( (float)boundingBox.x, (float)boundingBox.y ), boundingBox.width,
boundingBox.height, true, Mat() ) );
trajectory.push_back( initState );
maxCMLength = 10;
}
void TrackerBoostingModel::modelEstimationImpl( const std::vector<Mat>& responses )
{
responseToConfidenceMap( responses, currentConfidenceMap );
}
void TrackerBoostingModel::modelUpdateImpl()
{
}
void TrackerBoostingModel::setMode( int trainingMode, const std::vector<Mat>& samples )
{
currentSample.clear();
currentSample = samples;
mode = trainingMode;
}
std::vector<int> TrackerBoostingModel::getSelectedWeakClassifier()
{
return stateEstimator.staticCast<TrackerStateEstimatorAdaBoosting>()->computeSelectedWeakClassifier();
}
void TrackerBoostingModel::responseToConfidenceMap( const std::vector<Mat>& responses, ConfidenceMap& confidenceMap )
{
if( currentSample.empty() )
{
CV_Error( -1, "The samples in Model estimation are empty" );
}
for ( size_t i = 0; i < currentSample.size(); i++ )
{
Size currentSize;
Point currentOfs;
currentSample.at( i ).locateROI( currentSize, currentOfs );
bool foreground = false;
if( mode == MODE_POSITIVE || mode == MODE_CLASSIFY )
{
foreground = true;
}
else if( mode == MODE_NEGATIVE )
{
foreground = false;
}
const Mat resp = responses[0].col( (int)i );
//create the state
Ptr<TrackerStateEstimatorAdaBoosting::TrackerAdaBoostingTargetState> currentState = Ptr<
TrackerStateEstimatorAdaBoosting::TrackerAdaBoostingTargetState>(
new TrackerStateEstimatorAdaBoosting::TrackerAdaBoostingTargetState( currentOfs, currentSample.at( i ).cols, currentSample.at( i ).rows,
foreground, resp ) );
confidenceMap.push_back( std::make_pair( currentState, 0.0f ) );
}
}
}