ARuCo Tracking

A class for straightforward tracking with an ARuCo

class sksurgeryarucotracker.arucotracker.ArUcoTracker(configuration)

Bases: sksurgerycore.baseclasses.tracker.SKSBaseTracker

Initialises and Configures the ArUco detector

Parameters:configuration –

A dictionary containing details of the tracker.

video source: defaults to 0

aruco dictionary: defaults to DICT_4X4_50

marker size: defaults to 50 mm

camera projection: defaults to None

camera distortion: defaults to None

smoothing buffer: specify a buffer over which to average the tracking, defaults to 1

rigid bodies: a list of rigid bodies to track, each body should have a ‘name’, a ‘filename’ where the tag geometry is defined, and an ‘aruco dictionary’ to use. Additionally we can include ‘tag width’ in mm when the tag has been scaled during printing or is displayed on a mobile phone screen or similar

Raises:Exception – ImportError, ValueError

close()

Closes the connection to the Tracker and deletes the tracker device.

Raises:Exception – ValueError

get_frame(frame=None)

Gets a frame of tracking data from the Tracker device.

Parameters:frame – an image to process, if None, we use the OpenCV video source. Returns:port_numbers: If tools have been defined port numbers are the tool descriptions. Otherwise port numbers are the aruco tag ID prefixed with aruco

time_stamps : list of timestamps (cpu clock), one per tool

frame_numbers : list of framenumbers (tracker clock) one per tool

tracking : list of 4x4 tracking matrices, rotation and position,

tracking_quality : list the tracking quality, one per tool.

Raises:Exception – ValueError

get_tool_descriptions()

Returns tool descriptions

has_capture()

:Returns true if the tracker has it’s own opencv source otherwise false

start_tracking()

Tells the tracking device to start tracking. :raise Exception: ValueError

stop_tracking()

Tells the tracking devices to stop tracking. :raise Exception: ValueError

Register detected image points (2D) to model points (3D)

Classes and functions for 2D to 3D registration

sksurgeryarucotracker.algorithms.registration_2d3d.estimate_poses_no_calibration(marker_corners, aruco_board)

Returns tracking data for a camera with no calibration data. x and y are the screen pixel coordinates. z is based on the size of the tag in pixels, there is no rotation. No account is taken of the size of the model marker pattern, so it will be bit flakey.

sksurgeryarucotracker.algorithms.registration_2d3d.estimate_poses_with_calibration(marker_corners2d, marker_ids, aruco_board, camera_projection_matrix, camera_distortion)

Estimate the pose of a single tag or a multi-tag rigid body when the camera calibration is known. :param marker_corners2d: a list of 2d marker corners, 1 row per tag,

8 columns per tag

Parameters:

• model_points – Matched list of of corresponding model points, 1 row per tag, 15 columns per tag: corner points and centre point
• camera_projection_matrix – a 3x3 camera projection matrix
• camera_distortion – camera distortion vector

:return : a tracking rotation, translation and a quality

Manage rigid bodies consisting of multiple tags

Classes and functions for maintaining ArUco rigid bodies

class sksurgeryarucotracker.algorithms.rigid_bodies.ArUcoRigidBody(rigid_body_name)

Bases: object

Class to handle the loading and registering of ArUco Rigid Bodies

add_single_tag(tag_size, marker_id, dictionary)

We can use this to track single ArUco tags rather than patterns as long as we know the tag size in mm

Param:tag size in mm Param:marker id/_

get_dictionary_name()

returns the name of the aruco dictionary in use

get_pose(camera_projection_matrix, camera_distortion)

Estimate the pose of the rigid body, with or without camera calibration

Param:camera_projection_matrix 3x3 projection matrix. If None we estimate pose based on pattern size Param:1x5 camera distortion vector

load_3d_points(filename, dictionaryname)

Loads the 3D point geometry from a file

Parameters:filename – Path of file containing tag data

reset_2d_points()

Clears 2D point lists.

scale_3d_tags(measured_pattern_width)

We can scale the tag, which is very useful if you’ve got the tag on your mobile phone.

Parameters:measured_pattern_width – Width of the tag in mm

set_2d_points(two_d_points, tag_ids)

takes a list of 2 points, and if the id’s match 3D points, assigns them to a list of 2d points

Parameters:

• two_d_points – array of marker corners, 4 for each tag
• tag_ids – id for each tag

Returns:

tag ids for any assigned tags

class sksurgeryarucotracker.algorithms.rigid_bodies.Board(markerpoints, dictionary, marker_ids)

Bases: object

A local replacement for aruco.Board which was deprecated at 4.7

class sksurgeryarucotracker.algorithms.rigid_bodies.TwoDTags

Bases: object

Stores two linked arrays, on of tag IDs and the other 2D points

append_tag(tag_id, points)

Adds a tag to the two point list :param tag_id: The id of the tag :param points: 4 points defining the tag corners

sksurgeryarucotracker.algorithms.rigid_bodies.configure_rigid_bodies(configuration)

reads configuration and creates a list of rigid bodies together with a list of dictionaries used.

sksurgeryarucotracker.algorithms.rigid_bodies.load_board_from_file(filename, dictionary=16)

loads marker pattern from filename. :return: an aruco.board :raise ValueError: If the file does not have 16 or 13 columns

sksurgeryarucotracker.algorithms.rigid_bodies.scale_tags(board, measured_pattern_width)

We can scale the tag on a board, which is very useful if you’ve got the tag on your mobile phone.

Param:the board to scale Parameters:measured_pattern_width – Width of the tag in mm

sksurgeryarucotracker.algorithms.rigid_bodies.single_tag_board(tag_size, marker_id, dictionary=< cv2.aruco.Dictionary 0x7fd42e248c30>)

Create a board consisting of a single ArUco tag

Param:tag size in mm Param:marker id Param:dictionary to use