OpenCV
3.1.0
Open Source Computer Vision

Functions  
void  cv::sfm::reconstruct (InputArrayOfArrays points2d, OutputArray Ps, OutputArray points3d, InputOutputArray K, bool is_projective=false) 
Reconstruct 3d points from 2d correspondences while performing autocalibration. More...  
void  cv::sfm::reconstruct (InputArrayOfArrays points2d, OutputArray Rs, OutputArray Ts, InputOutputArray K, OutputArray points3d, bool is_projective=false) 
Reconstruct 3d points from 2d correspondences while performing autocalibration. More...  
void  cv::sfm::reconstruct (const std::vector< std::string > images, OutputArray Ps, OutputArray points3d, InputOutputArray K, bool is_projective=false) 
Reconstruct 3d points from 2d images while performing autocalibration. More...  
void  cv::sfm::reconstruct (const std::vector< std::string > images, OutputArray Rs, OutputArray Ts, InputOutputArray K, OutputArray points3d, bool is_projective=false) 
Reconstruct 3d points from 2d images while performing autocalibration. More...  
void cv::sfm::reconstruct  (  InputArrayOfArrays  points2d, 
OutputArray  Ps,  
OutputArray  points3d,  
InputOutputArray  K,  
bool  is_projective = false 

) 
Reconstruct 3d points from 2d correspondences while performing autocalibration.
points2d  Input vector of vectors of 2d points (the inner vector is per image). 
Ps  Output vector with the 3x4 projections matrices of each image. 
points3d  Output array with estimated 3d points. 
K  Input/Output camera matrix \(K = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\). Input parameters used as initial guess. 
is_projective  if true, the cameras are supposed to be projective. 
This method calls below signature and extracts projection matrices from estimated K, R and t.
void cv::sfm::reconstruct  (  InputArrayOfArrays  points2d, 
OutputArray  Rs,  
OutputArray  Ts,  
InputOutputArray  K,  
OutputArray  points3d,  
bool  is_projective = false 

) 
Reconstruct 3d points from 2d correspondences while performing autocalibration.
points2d  Input vector of vectors of 2d points (the inner vector is per image). 
Rs  Output vector of 3x3 rotations of the camera. 
Ts  Output vector of 3x1 translations of the camera. 
points3d  Output array with estimated 3d points. 
K  Input/Output camera matrix \(K = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\). Input parameters used as initial guess. 
is_projective  if true, the cameras are supposed to be projective. 
Internally calls libmv simple pipeline routine with some default parameters by instatiating SFMLibmvEuclideanReconstruction class.
void cv::sfm::reconstruct  (  const std::vector< std::string >  images, 
OutputArray  Ps,  
OutputArray  points3d,  
InputOutputArray  K,  
bool  is_projective = false 

) 
Reconstruct 3d points from 2d images while performing autocalibration.
images  a vector of string with the images paths. 
Ps  Output vector with the 3x4 projections matrices of each image. 
points3d  Output array with estimated 3d points. 
K  Input/Output camera matrix \(K = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\). Input parameters used as initial guess. 
is_projective  if true, the cameras are supposed to be projective. 
This method calls below signature and extracts projection matrices from estimated K, R and t.
void cv::sfm::reconstruct  (  const std::vector< std::string >  images, 
OutputArray  Rs,  
OutputArray  Ts,  
InputOutputArray  K,  
OutputArray  points3d,  
bool  is_projective = false 

) 
Reconstruct 3d points from 2d images while performing autocalibration.
images  a vector of string with the images paths. 
Rs  Output vector of 3x3 rotations of the camera. 
Ts  Output vector of 3x1 translations of the camera. 
points3d  Output array with estimated 3d points. 
K  Input/Output camera matrix \(K = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\). Input parameters used as initial guess. 
is_projective  if true, the cameras are supposed to be projective. 
Internally calls libmv simple pipeline routine with some default parameters by instatiating SFMLibmvEuclideanReconstruction class.