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//
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//                For Open Source Computer Vision Library
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//     this list of conditions and the following disclaimer.
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/** @file
@author Tolga Birdal <tbirdal AT gmail.com>
*/

#ifndef __OPENCV_SURFACE_MATCHING_POSE3D_HPP__
#define __OPENCV_SURFACE_MATCHING_POSE3D_HPP__

#include "opencv2/core/cvstd.hpp" // cv::Ptr
#include <vector>
#include <string>

namespace cv
{
namespace ppf_match_3d
{

//! @addtogroup surface_matching
//! @{

class Pose3D;
typedef Ptr<Pose3D> Pose3DPtr;

class PoseCluster3D;
typedef Ptr<PoseCluster3D> PoseCluster3DPtr;

/**
* @brief Class, allowing the storage of a pose. The data structure stores both
* the quaternions and the matrix forms. It supports IO functionality together with
* various helper methods to work with poses
*
*/
class CV_EXPORTS Pose3D
{
public:
  Pose3D()
  {
    alpha=0;
    modelIndex=0;
    numVotes=0;
    residual = 0;

    for (int i=0; i<16; i++)
      pose[i]=0;
  }

  Pose3D(double Alpha, unsigned int ModelIndex=0, unsigned int NumVotes=0)
  {
    alpha = Alpha;
    modelIndex = ModelIndex;
    numVotes = NumVotes;
    residual=0;

    for (int i=0; i<16; i++)
      pose[i]=0;
  }

  /**
   *  \brief Updates the pose with the new one
   *  \param [in] NewPose New pose to overwrite
   */
  void updatePose(double NewPose[16]);

  /**
   *  \brief Updates the pose with the new one
   */
  void updatePose(double NewR[9], double NewT[3]);

  /**
   *  \brief Updates the pose with the new one, but this time using quaternions to represent rotation
   */
  void updatePoseQuat(double Q[4], double NewT[3]);

  /**
   *  \brief Left multiplies the existing pose in order to update the transformation
   *  \param [in] IncrementalPose New pose to apply
   */
  void appendPose(double IncrementalPose[16]);
  void printPose();

  Pose3DPtr clone();

  int writePose(FILE* f);
  int readPose(FILE* f);
  int writePose(const std::string& FileName);
  int readPose(const std::string& FileName);

  virtual ~Pose3D() {}

  double alpha, residual;
  unsigned int modelIndex;
  unsigned int numVotes;
  double pose[16], angle, t[3], q[4];
};

/**
* @brief When multiple poses (see Pose3D) are grouped together (contribute to the same transformation) 
* pose clusters occur. This class is a general container for such groups of poses. It is possible to store,
* load and perform IO on these poses.
*/
class CV_EXPORTS PoseCluster3D
{
public:
  PoseCluster3D()
  {
    numVotes=0;
    id=0;
  }

  PoseCluster3D(Pose3DPtr newPose)
  {
    poseList.clear();
    poseList.push_back(newPose);
    numVotes=newPose->numVotes;
    id=0;
  }

  PoseCluster3D(Pose3DPtr newPose, int newId)
  {
    poseList.push_back(newPose);
    this->numVotes = newPose->numVotes;
    this->id = newId;
  }

  virtual ~PoseCluster3D()
  {}

  /**
   *  \brief Adds a new pose to the cluster. The pose should be "close" to the mean poses
   *  in order to preserve the consistency
   *  \param [in] newPose Pose to add to the cluster
   */
  void addPose(Pose3DPtr newPose);

  int writePoseCluster(FILE* f);
  int readPoseCluster(FILE* f);
  int writePoseCluster(const std::string& FileName);
  int readPoseCluster(const std::string& FileName);

  std::vector<Pose3DPtr> poseList;
  int numVotes;
  int id;
};

//! @}

} // namespace ppf_match_3d
} // namespace cv

#endif