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Published Articles >> Table of Contents >> Abstract
2006 IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS'06)
p. 92
Robust Auto-Calibration from Pedestrians
Imran Junejo, University of Central Florida, USA
Hassan Foroosh, University of Central Florida, USA
Full Article Text:
 
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AVSS.2006.99
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| Abstract |
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The knowledge of camera intrinsic and extrinsic parameters
is useful, as it allows us to make world measurements.
Unfortunately, calibration information is rarely available
in video surveillance systems and it is difficult to obtain
once the system is installed. Auto-calibrating cameras using
moving objects (humans) has recently attracted a lot of
interest. Two methods are proposed by Lv-Nevatia(2002)
and Krahnstoever-Mendonca(2005). The inherent difficulty
of the problem lies in the noise that is generally present in
the data. We propose a robust and a general linear solution
to the problem by adopting a formulation different from the
existing methods. The uniqueness of formulation lies in recognizing
two harmonic homologies present in the geometry
obtained by observing pedestrians, and then using properties
of these homologies to obtain linear constraints on the
unknown camera parameters. Experiments with synthetic
as well as on real data are presented - indicating the practicality
of the proposed system.
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 Additional Information
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Citation:
Imran Junejo, Hassan Foroosh,
"Robust Auto-Calibration from Pedestrians,"
avss,
p. 92,
2006 IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS'06),
2006
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