1. Structured Light Systems are often used in computer
vision to form accurate 3D models. These systems
include at least one or more camera, projector pairs.
Before these systems can be effectively implemented,
the projector and camera must first be calibrated.
Camera calibration has already been extensively studied,
while projector calibration is less established. An
effective structured light system calibration technique
called Huang’s method calibrates the projector in the
same way as a camera, thus simplifying the process.
Using Huang’s methods as a basis, we designed a quick,
accurate calibration technique that works with our
hardware and can eventually be implemented into a multi
camera, projector structured light system.
This work was supported by LentinkLab with
thanks to a generous grant from the Summer
Undergraduate Research Institute in the
Stanford University Department of Mechanical
Engineering.
[1] Bouguet 2013, “Camera Calibration Toolbox for
Matlab”,
[Online]: www.vision.caltech.edu/bouguetj/calib_doc/
[2] Falcao,
Gabriel,
Natalie
Hurtos,
and
Joan
Massich.
"Plane-­‐
based
Calibra<on
of
a
Projector-­‐camera
System."
VIBOT
Master
(2008):
1-­‐12.
2008.
Web.
24
Aug.
2016.
Unique Challenges
• Matlab code must be adapted for a specific
calibration system.
• Calibration technique must be easily integrated
into a multi-projector, camera system.
• New hardware must work together effectively.
Multi-camera, projector system
Alter calibration rig and Matlab code to allow for the
simultaneous calibration of four camera, projector
pairs.
Structured Light System Calibration
Nathan Petrie, Marc Deetjen, David Lentink
Lentink Lab, Department of Mechanical Engineering, Stanford University
2. Image Capturing
The
projector
projects
a
checkerboard
image
onto
the
checkerboard.
The
high-­‐speed
camera
captures
mul<ple
images
of
the
checkerboard
in
different
orienta<ons
while
the
projector
is
both
on
and
off.
3. Matlab Corner Clicking
Images are loaded into Matlab
where corners are extracted
( t h r o u g h c l i c k i n g ) . 2 D - 3 D
correspondences are created using
the images. Extrinsic and intrinsic
parameters of both the projector
and camera are then estimated.
Step
1:
Calibrate
Camera
(Find
Camera
Matrix
KC)
Projector
On
Projector
Off
Camera Number: 1, Image Number: 1
Bouguet 2000
Step
3:
Calibrate
Projector
(Find
Kp)
Step
2:
Find
the
3D
Coordinates
of
the
projected
pa[ern
The
structured
Light
system
is
used
to
create
a
3D
reconstruc<on
of
the
surface
of
a
bird.
The
system
must
first
be
calibrated.
The
calibra<on
method
must
be
adapted
to
fit
the
experiment
specifica<ons.
Goal: Find the Intrinsic and Extrinsic Parameters of the Projector and Camera
1. Set-up
Projector and camera are directed
towards a checkerboard. The
projector will project a pattern onto
the checkerboard while the high-
speed camera captures images of
the checkerboard.
High
Speed
Camera
Projector
Step
4:
Compute
Rota<on
and
Transla<on
(R,T)