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from mathutils import Vector
import bpy
import itertools
import re
from collections import defaultdict
bl_info = {
"name": "Resolve Camera Tracks",
"author": "Anthony Zhang",
"category": "Animation",
"version": (1, 1),
"blender": (2, 75, 0),
"location": "View3D > Object > Resolve Camera Tracks or Search > Resolve Camera Tracks",
"description": "3D point reconstruction from multiple camera angles",
class ResolveCameraTracks(bpy.types.Operator):
bl_idname = "animation.resolve_camera_tracks"
bl_label = "Resolve Camera Tracks"
bl_options = {"REGISTER", "UNDO"} # enable undo for operator
def execute(self, context):
targets = []
for obj in context.selected_objects:
if obj.type == "EMPTY":
else:{"ERROR_INVALID_INPUT"}, "Non-empty object \"{}\" selected".format(
return {"CANCELLED"}
# associate pairs of empties together by base name
targets_by_track_name = defaultdict(list)
for target in targets:
track, _ = self.get_target_track(target)
for name, point_targets in targets_by_track_name.items():
if len(point_targets) < 2:{"ERROR_INVALID_INPUT"}, "At least two objects associated with tracks named \"{}\" required, only one selected".format(name))
return {"CANCELLED"}
# add the resolved empties
resolved_empties = []
for point_targets in targets_by_track_name.values():
except Exception as e:
import traceback{"ERROR_INVALID_INPUT"}, traceback.format_exc())
return {"CANCELLED"}
# select the resolved empties
for empty in resolved_empties: = True
return {"FINISHED"}
def get_target_track(self, target):
Returns a motion tracking track associated with object `target` and
the camera associated with object `target`.
# find the follow track constraint and obtain the associated track
for constraint in target.constraints:
if constraint.type == "FOLLOW_TRACK":
track_constraint = constraint
if not track_constraint.clip:
raise Exception("Clip for constraint \"{}\" of \"{}\" not found".format(,
raise Exception("Follow Track constraint for \"{}\" not found".format(
# get the track for the track constraint on the target
for object in track_constraint.clip.tracking.objects:
for track in object.tracks:
if == track_constraint.track:
return track,
raise Exception("Track for constraint \"{}\" of \"{}\" not found".format(,
def get_target_locations(self, target):
Returns a list of positions in world space for object `target` for
frames that it is animated for (and None for frames that are not), the
camera associated with object `target`, the start frame, and the end
track, camera = self.get_target_track(target)
# obtain track information
# set of frame indices for enabled markers
marker_frames = {marker.frame for marker in track.markers if not marker.mute}
start_frame, end_frame = min(marker_frames), max(marker_frames)
# save the frame so we can restore it later
original_frame = bpy.context.scene.frame_current
# store object world locations for each frame
locations = []
for i in range(start_frame, end_frame + 1):
if i in marker_frames:
# move back to the original frame
return locations, camera, start_frame, end_frame
def add_resolved_empty(self, targets):
Adds an empty animated to be at the point closest to every target in
`targets`, where each target in `targets` is animated by a Follow
Track constraint.
Returns the newly created empty.
# obtain target information
target_points, target_cams, target_starts, target_ends = [], [], [], []
for target in targets:
points, cam, start, end = self.get_target_locations(target)
target_points.append(points + [None]) # the last element must be None
# two camera is the minimum number of cameras
if len(set(target_cams)) < 2:
raise Exception("At least 2 cameras need to be available")
# add the empty object
resolved = bpy.context.active_object
# save the frame so we can restore it later
original_frame = bpy.context.scene.frame_current
# set up keyframes for each location
min_distance, min_distance_frame = float("inf"), None
max_distance, max_distance_frame = 0, None
for frame in range(min(target_starts), max(target_ends)):
# clamp indices to the last value, None, if outside of range
indices = []
for start, end in zip(target_starts, target_ends):
index = frame - start
indices.append(-1 if index < 0 or index > end - start else index)
bpy.context.scene.frame_set(frame) # move to the current frame
# go through each possible combination of targets and find the one
# that gives the best result
best_location, best_distance = None, float("inf")
for pair in itertools.combinations(range(0, len(targets)), 2):
first, second = pair[0], pair[1]
cam1, cam2 = target_cams[first].location, target_cams[second].location
location1, location2 = target_points[first][indices[first]], target_points[second][indices[second]]
if location1 is not None and location2 is not None:
location, distance = closest_point(cam1, cam2, location1, location2)
if distance < best_distance: # better result than current best
best_distance = distance
best_location = location
# add keyframe if possible
if best_location != None:
resolved.location = best_location
if best_distance <= min_distance:
min_distance = best_distance
min_distance_frame = frame
if best_distance >= max_distance:
max_distance = best_distance
max_distance_frame = frame
# move back to the original frame
# make the resolved track object more identifiable
track, _ = self.get_target_track(targets[0]) = "{}_tracked".format(
resolved.empty_draw_type = "SPHERE"
resolved.empty_draw_size = 0.1{"INFO"}, "{}: min error {} (frame {}), max error {} (frame {})".format(, min_distance / 2, min_distance_frame, max_distance / 2, max_distance_frame))
return resolved
def closest_point(cam1, cam2, point1, point2):
Produces the point closest to the lines formed from `cam1` to `point1` and
from `cam2` to `point2`, and the total distance between this point and the
dir1 = point1 - cam1
dir2 = point2 - cam2
dir3 = cam2 - cam1
a = dir1 * dir1
b = -dir1 * dir2
c = dir2 * dir2
d = dir3 * dir1
e = -dir3 * dir2
if abs((c * a) - (b ** 2)) < 0.0001: # lines are nearly parallel
raise Exception("Lines are too close to parallel")
extent1 = ((d * c) - (e * b)) / ((c * a) - (b ** 2))
extent2 = (e - (b * extent1)) / c
point1 = cam1 + (extent1 * dir1)
point2 = cam2 + (extent2 * dir2)
return (point1 + point2) / 2, (point1 - point2).magnitude
def add_object_button(self, context):
text="Resolve Camera Tracks", icon="PLUGIN")
def register():
def unregister():
if __name__ == "__main__":