3D Reconstruction🔗
On this topic🔗
Binocular Stereo🔗
binocular_disparity: Compute the disparities of a rectified image pair using correlation
techniques.
binocular_disparity_mg: Compute the disparities of a rectified stereo image pair using multigrid
methods.
binocular_disparity_ms: Compute the disparities of a rectified stereo image pair using
multi-scanline optimization.
binocular_distance: Compute the distance values for a rectified stereo image pair using
correlation techniques.
binocular_distance_mg: Compute the distance values for a rectified stereo image pair using
multigrid methods.
binocular_distance_ms: Compute the distance values for a rectified stereo image pair using
multi-scanline optimization.
disparity_image_to_xyz: Transform a disparity image into 3D points in a rectified stereo
system.
disparity_to_distance: Transform a disparity value into a distance value in a rectified
binocular stereo system.
disparity_to_point_3d: Transform an image point and its disparity into a 3D point in a
rectified stereo system.
distance_to_disparity: Transform a distance value into a disparity in a rectified stereo
system.
essential_to_fundamental_matrix: Compute the fundamental matrix from an essential matrix.
gen_binocular_proj_rectification: Compute the projective rectification of weakly calibrated binocular
stereo images.
gen_binocular_rectification_map: Generate transformation maps that describe the mapping of the images
of a binocular camera pair to a common rectified image plane.
intersect_lines_of_sight: Get a 3D point from the intersection of two lines of sight
within a binocular camera system.
match_essential_matrix_ransac: Compute the essential matrix for a pair of stereo images by automatically
finding correspondences between image points.
match_fundamental_matrix_distortion_ransac: Compute the fundamental matrix and the radial distortion coefficient
for a pair of stereo images by automatically finding correspondences
between image points.
match_fundamental_matrix_ransac: Compute the fundamental matrix for a pair of stereo images by
automatically finding correspondences between image
points.
match_rel_pose_ransac: Compute the relative orientation between two cameras by automatically
finding correspondences between image points.
reconst3d_from_fundamental_matrix: Compute the projective 3d reconstruction of points based on the fundamental
matrix.
rel_pose_to_fundamental_matrix: Compute the fundamental matrix from the relative orientation of two
cameras.
vector_to_essential_matrix: Compute the essential matrix given image point correspondences
and known camera matrices and reconstruct 3D points.
vector_to_fundamental_matrix: Compute the fundamental matrix given a set of image point
correspondences and reconstruct 3D points.
vector_to_fundamental_matrix_distortion: Compute the fundamental matrix and the radial distortion coefficient
given a set of image point correspondences and reconstruct 3D
points.
vector_to_rel_pose: Compute the relative orientation between two cameras given image point
correspondences and known camera parameters and reconstruct 3D space points.
Depth From Focus🔗
depth_from_focus: Extract depth using multiple focus levels.
select_grayvalues_from_channels: Selection of gray values of a multi-channel image using an index image.
Multi-View Stereo🔗
clear_stereo_model: Free the memory of a stereo model.
create_stereo_model: Create a HALCON stereo model.
get_stereo_model_image_pairs: Return the list of image pairs set in a stereo model.
get_stereo_model_object: Get intermediate iconic results of a stereo reconstruction.
get_stereo_model_object_model_3d: Get intermediate 3D object model of a stereo reconstruction
get_stereo_model_param: Get stereo model parameters.
reconstruct_points_stereo: Reconstruct 3D points from calibrated multi-view stereo images.
reconstruct_surface_stereo: Reconstruct surface from calibrated multi-view stereo images.
set_stereo_model_image_pairs: Specify image pairs to be used for surface stereo reconstruction.
set_stereo_model_param: Set stereo model parameters.
Photometric Stereo🔗
estimate_al_am: Estimate the albedo of a surface and the amount of ambient light.
estimate_sl_al_lr: Estimate the slant of a light source and the albedo of a surface.
estimate_sl_al_zc: Estimate the slant of a light source and the albedo of a surface.
estimate_tilt_lr: Estimate the tilt of a light source.
estimate_tilt_zc: Estimate the tilt of a light source.
photometric_stereo: Reconstruct a surface according to the photometric stereo technique.
reconstruct_height_field_from_gradient: Reconstruct a surface from surface gradients.
sfs_mod_lr: Reconstruct a surface from a gray value image.
sfs_orig_lr: Reconstruct a surface from a gray value image.
sfs_pentland: Reconstruct a surface from a gray value image.
shade_height_field: Shade a height field.
uncalibrated_photometric_stereo: Reconstruct a surface from several, differently illuminated images.
Sheet Of Light🔗
apply_sheet_of_light_calibration: Apply the calibration transformations to the input disparity image.
calibrate_sheet_of_light: Calibrate a sheet-of-light setup with a 3D calibration object.
clear_sheet_of_light_model: Delete a sheet-of-light model and free the allocated memory.
create_sheet_of_light_calib_object: Create a calibration object for sheet-of-light calibration.
create_sheet_of_light_model: Create a model to perform 3D-measurements using the sheet-of-light
technique.
deserialize_sheet_of_light_model: Deserialize a sheet-of-light model.
get_sheet_of_light_param: Get the value of a parameter, which has been set in a sheet-of-light model.
get_sheet_of_light_result: Get the iconic results of a measurement performed with the sheet-of light
technique.
get_sheet_of_light_result_object_model_3d: Get the result of a calibrated measurement performed with the
sheet-of-light technique as a 3D object model.
measure_profile_sheet_of_light: Process the profile image provided as input and store the resulting
disparity to the sheet-of-light model.
query_sheet_of_light_params: For a given sheet-of-light model get the names of the generic iconic
or control parameters that can be used in the different
sheet-of-light operators.
read_sheet_of_light_model: Read a sheet-of-light model from a file and create a new model.
reset_sheet_of_light_model: Reset a sheet-of-light model.
serialize_sheet_of_light_model: Serialize a sheet-of-light model.
set_profile_sheet_of_light: Set sheet of light profiles by measured disparities.
set_sheet_of_light_param: Set selected parameters of the sheet-of-light model.
write_sheet_of_light_model: Write a sheet-of-light model to a file.