PuReST.h

/*
 * Copyright (c) 2018, Thiago Santini
 *
 * Permission to use, copy, modify, and distribute this software and its
 * documentation for non-commercial purposes, without fee, and without a written
 * agreement is hereby granted, provided that:
 *
 * 1) the above copyright notice, this permission notice, and the subsequent
 * bibliographic references be included in all copies or substantial portions of
 * the software
 *
 * 2) the appropriate bibliographic references be made on related publications
 *
 * In this context, non-commercial means not intended for use towards commercial
 * advantage (e.g., as complement to or part of a product) or monetary
 * compensation. The copyright holder reserves the right to decide whether a
 * certain use classifies as commercial or not. For commercial use, please contact
 * the copyright holders.
 *
 * REFERENCES:
 *
 * Thiago Santini, Wolfgang Fuhl, Enkelejda Kasneci, PuReST: Robust pupil tracking
 * for real-time pervasive eye tracking, Symposium on Eye Tracking Research and
 * Applications (ETRA), 2018, https://doi.org/10.1145/3204493.3204578.
 *
 * Thiago Santini, Wolfgang Fuhl, Enkelejda Kasneci, PuRe: Robust pupil detection
 * for real-time pervasive eye tracking, Computer Vision and Image Understanding,
 * 2018, ISSN 1077-3142, https://doi.org/10.1016/j.cviu.2018.02.002.
 *
 *
 * IN NO EVENT SHALL THE AUTHORS BE LIABLE TO ANY PARTY FOR DIRECT,
 * INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS,
 * ARISING OUT OF THE USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF
 * THE AUTHORS HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 *
 * THE AUTHORS SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT LIMITED
 * TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
 * PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE AUTHORS
 * HAVE NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR
 * MODIFICATIONS.
*/

#ifndef PUREST_H
#define PUREST_H

#include "pupil-tracking/PupilTrackingMethod.h"
#include "pupil-detection/PuRe.h"

class GreedyCandidate
{

public:
	GreedyCandidate(const std::vector<cv::Point> &points) :
		points(points)
	{
		cv::convexHull(points, hull);
		maxGap = 0;
		meanPoint = {0, 0};
		for (auto p1=hull.begin(); p1!=hull.end(); p1++) {
			meanPoint += cv::Point2f(*p1);
			for (auto p2=p1+1; p2!=hull.end(); p2++) {
				float gap = norm(*p2-*p1);
				if (gap > maxGap)
					maxGap = gap;
			}
		}
		meanPoint.x /= points.size();
		meanPoint.y /= points.size();
	}

	float maxGap;
	std::vector<cv::Point> points;
	std::vector<cv::Point> hull;
	cv::Point2f meanPoint;

};

class PuReST : public PupilTrackingMethod, private PuRe
{

public:
	PuReST() {
		PupilTrackingMethod::mDesc = desc;
		openKernel = cv::getStructuringElement( cv::MORPH_ELLIPSE, {7,7} );
		dilateKernel = cv::getStructuringElement( cv::MORPH_ELLIPSE, {15,15} );
	}
	static std::string desc;
	void run(const cv::Mat &frame, const cv::Rect &roi, const Pupil &previousPupil, Pupil &pupil, const float &userMinPupilDiameterPx=-1, const float &userMaxPupilDiameterPx=-1);

private:
	void calculateHistogram(const cv::Mat &in, cv::Mat &histogram, const int &bins, const cv::Mat &mask = cv::Mat());
	void getThresholds(const cv::Mat &input, const cv::Mat &histogram, const Pupil &pupil, int &lowTh, int &highTh, cv::Mat &bright, cv::Mat &dark);
	cv::Mat dilateKernel;
    cv::Mat openKernel;
    Pupil outlineSeedPupil;

    bool greedySearch(const cv::Mat &greedyDetectorEdges, const Pupil &basePupil, const cv::Mat &dark, const cv::Mat &bright, Pupil &pupil, const float &localMinPupilDiameterPx);
	bool trackOutline(const cv::Mat &outlineTrackerEdges, const Pupil &basePupil, Pupil &pupil, const float &localScalingRatio, const float &minOutlineConfidence = 0.65f);
	void generateCombinations(const std::vector<GreedyCandidate> &seeds, std::vector<GreedyCandidate> &candidates, const int length);
	float confidence(const cv::Mat frame, const Pupil &pupil, const std::vector<cv::Point> points);
};

#endif // PUREST_H