sksurgerycalibration.video.video_calibration_cost_functions module

Cost functions for video calibration, used with scipy.

sksurgerycalibration.video.video_calibration_cost_functions.mono_proj_err_h2e(x_0, object_points, image_points, intrinsics, distortion, pattern_tracking, device_tracking, pattern2marker_matrix)

Computes the SSE of projected image points and actual image points, for a single camera, where we have a tracked calibration pattern, and assume the pattern2marker transform should remain fixed. Therefore we only optimise hand-eye. So, x_0 should be of length 6.

sksurgerycalibration.video.video_calibration_cost_functions.mono_proj_err_h2e_g2w(x_0, object_points, image_points, intrinsics, distortion, device_tracking)

Method to the SSE of projected image points to actual image points, for a single camera, where we have an untracked pattern. Both the hand2eye and grid2world are optimised. So, x_0 should be of length 12.

sksurgerycalibration.video.video_calibration_cost_functions.mono_proj_err_h2e_int_dist(x_0, object_points, image_points, device_tracking, pattern_tracking, pattern2marker_matrix)

Computes the SSE between projected image points to actual image points, for a single camera, where we have a tracked pattern. The handeye, intrinsics and distortion parameters are optimised. So, x_0 should be of length 6+4+5 = 15.

sksurgerycalibration.video.video_calibration_cost_functions.mono_proj_err_p2m_h2e(x_0, object_points, image_points, intrinsics, distortion, pattern_tracking, device_tracking)

Computes the SSE between projected image points to actual image points, for a single camera, where we have a tracked pattern. Both the pattern2marker and hand2eye are optimised. So, x_0 should be of length 12.

sksurgerycalibration.video.video_calibration_cost_functions.stereo_2d_error_for_extrinsics(x_0, common_object_points, common_left_image_points, common_right_image_points, left_intrinsics, left_distortion, right_intrinsics, right_distortion, l2r_rmat, l2r_tvec)

Computes a vector of residuals between projected image points and actual image points, for left and right image. x_0 should contain left camera extrinsic parameters.

sksurgerycalibration.video.video_calibration_cost_functions.stereo_proj_err_h2e(x_0, common_object_points, common_left_image_points, common_right_image_points, left_intrinsics, left_distortion, right_intrinsics, right_distortion, l2r_rmat, l2r_tvec, device_tracking_array, pattern_tracking_array, left_pattern2marker_matrix=None)

Computes the SSE of projected image points and actual image points for left and right cameras. x_0 should contain the 6DOF of hand-to-eye, and if left_pattern2marker_matrix is None, then an additional 6DOF of pattern-to-marker. So, x_0 can be either length 6 or length 12.

Parameters:

• x_0 –
• common_object_points –
• common_left_image_points –
• common_right_image_points –
• left_intrinsics –
• left_distortion –
• right_intrinsics –
• right_distortion –
• l2r_rmat –
• l2r_tvec –
• device_tracking_array –
• pattern_tracking_array –
• left_pattern2marker_matrix –

Returns:

matrix of residuals for Levenberg-Marquardt optimisation.

sksurgerycalibration.video.video_calibration_cost_functions.stereo_proj_err_h2e_int_dist_l2r(x_0, common_object_points, common_left_image_points, common_right_image_points, device_tracking_array, pattern_tracking_array, left_pattern2marker_matrix)

Computes the SSE of projected image points against actual image points. x_0 should be 30 DOF.