polyora/mserdetector.cpp

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/*  This file is part of Polyora, a multi-target tracking library.
    Copyright (C) 2010 Julien Pilet

    This program is free software; you can redistribute it and/or modify
    it under the terms of the GNU General Public License as published by
    the Free Software Foundation; either version 2 of the License, or
    (at your option) any later version.

    This program is distributed in the hope that it will be useful,
    but WITHOUT ANY WARRANTY; without even the implied warranty of
    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
    GNU General Public License for more details.

    You should have received a copy of the GNU General Public License along
    with this program. If not, see <http://www.gnu.org/licenses/>.

    To contact the author of this program, please send an e-mail to:
    julien.pilet(at)calodox.org
*/
#include "mserdetector.h"

MSERDetector::MSERDetector() : storage(cvCreateMemStorage(0)), mean(cv::Size(2,1))
{
        params = cvMSERParams();
        params.minArea=3;
        params.delta=5;
        params.minDiversity=0.7;
        params.maxVariation = .15;
        params.maxArea=300;
}

unsigned MSERDetector::mser(cv::Mat &mat, cv::Mat mask)
{
        CvMat _image = mat, _mask, *maskp=0;
        if (mask.data) {
                _mask = mask;
                maskp = &_mask;
        }

        // mark previously allocated memory as available.
        // invalidates previous contours.
        cvClearMemStorage(storage);
        cvExtractMSER(&_image, maskp, &contours.seq, storage, params );

        return size();
}

void MSERDetector::getRegion(Contour &contour, MSERegion &r)
{
        int n =contour.size();
        cv::Mat_<float> dat(cv::Size(2,n));
        float *ptr= &dat(0,0);
        mean(0,0)=mean(0,1)=0;
        for (cv::Seq<cv::Point>::iterator j(contour.begin()); --n>=0; ++j) {
                mean(0,0) += ptr[0] = (*j).x;
                mean(0,1) += ptr[1] = (*j).y;
                ptr+=2;
        }
        mean *= 1.0/contour.size();
        r.c.x = mean.at<float>(0,0), r.c.y = mean.at<float>(0,1);

        pca(dat, mean, CV_PCA_DATA_AS_ROW, 2);

        float a = 1.5f*sqrtf(pca.eigenvalues.at<float>(0,0));
        float b = 1.5f*sqrtf(pca.eigenvalues.at<float>(0,1));
        cv::Point_<float> e1(a*pca.eigenvectors.at<float>(0,0), a*pca.eigenvectors.at<float>(0,1));
        cv::Point_<float> e2(b*pca.eigenvectors.at<float>(1,0), b*pca.eigenvectors.at<float>(1,1));

        if (e1.x*e2.y-e1.y*e2.x<0) {
                e2 = -e2;
        }
        r.e1 = e1;
        r.e2 = e2;
}

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