Multi camera measurement systems are widely used to extract information about the 3D configuration
or &ldquo / state&rdquo / of one or more real world objects. Camera calibration is the process of
pre-determining all the remaining optical and geometric parameters of the measurement system
which are either static or slowly varying. For a single camera, this consist of the internal
parameters of the camera device optics and construction while for a multiple camera system,
it also includes the geometric positioning of the individual cameras, namely &ldquo / external&rdquo / parameters.
The calibration is a necessary step before any actual state measurements can be
made from the system. In this thesis, such a multi-camera state measurement system and in
particular the problem of procedurally effective and high performance calibration of such a
system is considered.
This thesis presents a novel calibration algorithm which uses the known dynamics of a ballistically
thrown target object and employs the Extended Kalman Filter (EKF) to calibrate the
multi-camera system. The state-space representation of the target state is augmented with the
unknown calibration parameters which are assumed to be static or slowly varying with respect
to the state. This results in a &ldquo / super-state&rdquo / vector. The EKF algorithm is used to recursively
estimate this super-state hence resulting in the estimates of the static camera parameters. It is
demonstrated by both simulation studies as well as actual experiments that when the ballistic
path of the target is processed by the improved versions of the EKF algorithm, the camera calibration
parameter estimates asymptotically converge to their actual values. Since the image
frames of the target trajectory can be acquired first and then processed off-line, subsequent
improvements of the EKF algorithm include repeated and bidirectional versions where the
same calibration images are repeatedly used. Repeated EKF (R-EKF) provides convergence
with a limited number of image frames when the initial target state is accurately provided
while its bidirectional version (RB-EKF) improves calibration accuracy by also estimating
the initial target state.
The primary contribution of the approach is that it provides a fast calibration procedure where
there is no need for any standard or custom made calibration target plates covering the majority
of camera field-of-view. Also, human assistance is minimized since all frame data is
processed automatically and assistance is limited to making the target throws. The speed of
convergence and accuracy of the results promise a field-applicable calibration procedure.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/3/12609798/index.pdf |
| Date | 01 August 2008 |
| Creators | Aykin, Murat Deniz |
| Contributors | Saranli, Afsar |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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