/*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" ); return; } 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 ) ); } } }