[Colloquium] Reminder: TTI-C Guest Speaker Today 6/28/05 Barreto

[Katherine Cumming]

Joao P. Barreto 
University of Pennsylvania-GRASP Laboratory,
http://www.cis.upenn.edu/~jpbar/cabecalho.htm
The Fundamental Matrix for Cameras with Radial Distortion
Tuesday, June 28, 2005 12:00pm - Lunch Provided
TTI-C Conference Room 
Abstract:
Application in the Calibration of Wide Area Camera Networks 

The multiple view geometry on the context of camera self- calibration
and structure from motion has been deeply studied and is subject for
textbooks. However, most of the work in the topic assumes that the
camera follows the pin-hole model. This is not the case for many vision
sensors that are broadly used in everyday applications. Some examples
are the cameras with wide-angle lenses or motorized zoom where the lens
radial distortion, caused by the bending of the light rays when crossing
the optics, introduces a non-linearity in the image formation model.
Since these cameras deviate from the pin-hole model, the application of
uncalibrated stereo usually requires a partial calibration to determine
the non-linear relation between the image and the space coordinates.
When deploying a heterogeneous camera network or when we using cheap
zoom cameras like in cell-phones, it is not practical, if not impossible
to off-line calibrate the radial distortion of each camera using
reference objects. It is rather desirable to have an automatic procedure
without strong assumptions about the scene. 

In this work, we present a new algorithm for estimating the epipolar
geometry of two views where the two views can be radially distorted with
different distortion factors. Points in the projective plane are lifted
to a quadric in the three-dimensional projective space. It is shown that
the non-linear distortion in the projective plane results to a matrix
transformation in the space of lifted coordinates. The new epipolar
constraint depends linearly on a 4x4 radial fundamental matrix (RFM)
that encodes both the standard fundamental matrix (SFM) and the
distortion parameters. Like the SFM, the RFM is a projective correlation
that maps lifted points in one view into epipolar curves in the other
view. We propose a linear algorithm that computes the RFM using a
minimum of 15 image correspondences. We automatically detect outliers
using a RANSAC based approach, and present experimental results on real
imagery.

In the second part of the talk we overview our current research in
tele-immersion. Tele-immersion is a new paradigm for communication that
associates 3D reconstruction with computer graphics, networking and
media technologies. The objective is to create a medium for groups of
people remote from each other to work and share experiences together in
an immersive 3D virtual environment. We present our toolbox to calibrate
the wide area camera networks that are required for the data
acquisition. The proposed approach is based in a factorization method
that does not involve non-linear minimization. 
If you have questions, or would like to meet the speaker, please contact
Katherine at 773-834-1994 or kcumming at tti-c.org. For information on
future TTI-C talks or events, please go to the TTI-C Events
<http://ttic.uchicago.edu/events/events_dyn.php>  page. 
 
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