vpRBSilhouetteCCDTracker.h

/*
 * ViSP, open source Visual Servoing Platform software.
 * Copyright (C) 2005 - 2024 by Inria. All rights reserved.
 *
 * This software 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.
 * See the file LICENSE.txt at the root directory of this source
 * distribution for additional information about the GNU GPL.
 *
 * For using ViSP with software that can not be combined with the GNU
 * GPL, please contact Inria about acquiring a ViSP Professional
 * Edition License.
 *
 * See https://visp.inria.fr for more information.
 *
 * This software was developed at:
 * Inria Rennes - Bretagne Atlantique
 * Campus Universitaire de Beaulieu
 * 35042 Rennes Cedex
 * France
 *
 * If you have questions regarding the use of this file, please contact
 * Inria at visp@inria.fr
 *
 * This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE
 * WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.
 */
 
#ifndef VP_SILHOUETTE_CCD_TRACKER_H
#define VP_SILHOUETTE_CCD_TRACKER_H
 
#include <visp3/core/vpConfig.h>
#include <visp3/core/vpColVector.h>
#include <visp3/core/vpImage.h>
#include <visp3/core/vpCameraParameters.h>
#include <visp3/core/vpExponentialMap.h>
#include <visp3/core/vpPixelMeterConversion.h>
#include <visp3/core/vpMatrix.h>
#include <visp3/core/vpHomogeneousMatrix.h>
#include <visp3/core/vpRobust.h>
 
// #if defined(VISP_HAVE_SIMDLIB)
// #include <Simd/SimdLib.h>
// #endif
#include <visp3/rbt/vpRBSilhouetteControlPoint.h>
#include <visp3/rbt/vpRBFeatureTracker.h>
 
#include <vector>
#include <iostream>
#include <algorithm>
 
#if defined(VISP_HAVE_NLOHMANN_JSON)
#include VISP_NLOHMANN_JSON(json.hpp)
#endif
 
BEGIN_VISP_NAMESPACE
 
 
enum vpRBSilhouetteCCDDisplayType
{
  SIMPLE = 0,
  WEIGHT = 1,
  ERROR = 2,
  INVALID = 3
};
 
class VISP_EXPORT vpCCDParameters
{
public:
  vpCCDParameters() : gamma_1(0.5), gamma_2(4), gamma_3(4), gamma_4(3), alpha(1.3), beta(0.06), kappa(0.5), covarianceIterDecreaseFactor(0.25), h(40), delta_h(1), phi_dim(6)
  { }
 
 
  ~vpCCDParameters() = default;
  double gamma_1;
  double gamma_2;
  double gamma_3;
  double gamma_4;
  double alpha;
  double beta;
 
  double kappa;
  double covarianceIterDecreaseFactor;
  int h;
  int delta_h;
  int phi_dim;
};
 
#if defined(VISP_HAVE_NLOHMANN_JSON)
inline void from_json(const nlohmann::json &j, vpCCDParameters &ccdParameters)
{
  ccdParameters.alpha = j.value("alpha", ccdParameters.alpha);
  ccdParameters.beta = j.value("beta", ccdParameters.beta);
  ccdParameters.kappa = j.value("kappa", ccdParameters.kappa);
  ccdParameters.covarianceIterDecreaseFactor = j.value("covarianceIterDecreaseFactor",
                                                      ccdParameters.covarianceIterDecreaseFactor);
  ccdParameters.h = j.value("h", ccdParameters.h);
  ccdParameters.delta_h = j.value("delta_h", ccdParameters.delta_h);
  ccdParameters.phi_dim = j.value("phi_dim", ccdParameters.phi_dim);
  if (j.contains("gamma")) {
    nlohmann::json gammaj = j["gamma"];
    if (!gammaj.is_array() || gammaj.size() != 4) {
      throw vpException(vpException::ioError, "CCD parameters: tried to read gamma values from something that is not a 4-sized float array");
    }
    ccdParameters.gamma_1 = gammaj[0];
    ccdParameters.gamma_2 = gammaj[1];
    ccdParameters.gamma_3 = gammaj[2];
    ccdParameters.gamma_4 = gammaj[3];
  }
}
#endif
 
class VISP_EXPORT vpCCDStatistics
{
public:
  vpMatrix vic; 
  vpMatrix mean_vic; 
  vpMatrix cov_vic; 
  vpMatrix nv; 
  vpMatrix imgPoints; 
  vpMatrix weight; 
 
  void reinit(int resolution, unsigned normalPointsNumber)
  {
    nv.resize(resolution, 2, false, false);
    mean_vic.resize(resolution, 6, false, false);
    cov_vic.resize(resolution, 18, false, false);
    vic.resize(resolution, 20 * normalPointsNumber, false, false);
    imgPoints.resize(resolution, 2 * 3 * normalPointsNumber, false, false);
    weight.resize(resolution, 2 * normalPointsNumber, false, false);
  }
};
 
class VISP_EXPORT vpRBSilhouetteCCDTracker : public vpRBFeatureTracker
{
public:
 
  vpRBSilhouetteCCDTracker();
  virtual ~vpRBSilhouetteCCDTracker() = default;
 
  bool requiresRGB() const VP_OVERRIDE { return true; }
  bool requiresDepth() const VP_OVERRIDE { return false; }
  bool requiresSilhouetteCandidates() const VP_OVERRIDE { return true; }
 
  void setCCDParameters(const vpCCDParameters &parameters) { m_ccdParameters = parameters; }
  vpCCDParameters getCCDParameters() const { return m_ccdParameters; }
  //void computeMask(const vpImage<vpRGBa> &render, vpCCDStatistics &stats);
 
  double getTemporalSmoothingFactor() const { return m_temporalSmoothingFac; }
  void setTemporalSmoothingFactor(double factor)
  {
    if (factor < 0.0) {
      throw vpException(vpException::badValue, "Temporal smoothing factor should be equal to or greater than 0");
    }
    m_temporalSmoothingFac = factor;
 
  }
 
  bool shouldUseMask() const { return m_useMask; }
  void setShouldUseMask(bool useMask) { m_useMask = useMask; }
 
  float getMinimumMaskConfidence() const { return m_minMaskConfidence; }
  void setMinimumMaskConfidence(float confidence)
  {
 
    m_minMaskConfidence = confidence;
  }
 
  void setDisplayType(vpRBSilhouetteCCDDisplayType type)
  {
    m_displayType = type;
  }
 
  void onTrackingIterStart() VP_OVERRIDE { }
  void onTrackingIterEnd() VP_OVERRIDE { }
 
  double getVVSTrackerWeight() const VP_OVERRIDE { return m_userVvsWeight / (10 * m_error.size()); }
 
  void extractFeatures(const vpRBFeatureTrackerInput &frame, const vpRBFeatureTrackerInput &previousFrame, const vpHomogeneousMatrix &cMo) VP_OVERRIDE;
  void trackFeatures(const vpRBFeatureTrackerInput & /*frame*/, const vpRBFeatureTrackerInput & /*previousFrame*/, const vpHomogeneousMatrix & /*cMo*/) VP_OVERRIDE { }
 
  void initVVS(const vpRBFeatureTrackerInput &frame, const vpRBFeatureTrackerInput &previousFrame, const vpHomogeneousMatrix &cMo) VP_OVERRIDE;
  void computeVVSIter(const vpRBFeatureTrackerInput &frame, const vpHomogeneousMatrix &cMo, unsigned int iteration) VP_OVERRIDE;
  void updateCovariance(const double /*lambda*/) VP_OVERRIDE
  {
    m_cov = m_sigma;
  }
 
  void display(const vpCameraParameters &cam, const vpImage<unsigned char> &I, const vpImage<vpRGBa> &IRGB, const vpImage<unsigned char> &depth) const VP_OVERRIDE;
 
#if defined(VISP_HAVE_NLOHMANN_JSON)
  virtual void loadJsonConfiguration(const nlohmann::json &j) VP_OVERRIDE
  {
    vpRBFeatureTracker::loadJsonConfiguration(j);
 
    m_vvsConvergenceThreshold = j.value("convergenceThreshold", m_vvsConvergenceThreshold);
    setTemporalSmoothingFactor(j.value("temporalSmoothing", m_temporalSmoothingFac));
    setShouldUseMask(j.value("useMask", m_useMask));
    setMinimumMaskConfidence(j.value("minMaskConfidence", m_minMaskConfidence));
 
    m_ccdParameters = j.value("ccd", m_ccdParameters);
  }
 
#endif
 
protected:
  void updateCCDPoints(const vpHomogeneousMatrix &cMo);
  void computeLocalStatistics(const vpImage<vpRGBa> &I, vpCCDStatistics &stats);
  void computeErrorAndInteractionMatrix();
  double computeMaskGradient(const vpImage<float> &mask, const vpRBSilhouetteControlPoint &pccd) const;
 
 
  vpCCDParameters m_ccdParameters;
 
  std::vector<vpRBSilhouetteControlPoint> m_controlPoints; 
  vpRobust m_robust;
 
  vpCCDStatistics m_stats;
  vpCCDStatistics m_prevStats;
 
  vpMatrix m_sigma;
 
  double m_vvsConvergenceThreshold;
  double tol;
 
  std::vector<vpColVector> m_gradients;
  std::vector<vpMatrix> m_hessians;
  vpColVector m_gradient; 
  vpMatrix m_hessian; 
  double m_temporalSmoothingFac; 
 
  bool m_useMask;
  double m_minMaskConfidence;
 
  vpRBSilhouetteCCDDisplayType m_displayType;
};
 
END_VISP_NAMESPACE
 
#endif