Calibrating Distributed Camera Networks
Devarajan, D.
Zhaolin Cheng
Radke, R.J.
Dept. of Electr., Rensselaer Polytech. Inst., Troy, NY;
This paper appears in: Proceedings of the IEEE
Publication Date: Oct. 2008
Volume: 96,
Issue: 10
On page(s): 1625-1639
ISSN: 0018-9219
INSPEC Accession Number: 10291056
Digital Object Identifier: 10.1109/JPROC.2008.928759
First Published: 2008-10-17
Current Version Published: 2008-10-31
Abstract
Recent developments in wireless sensor networks have made feasible distributed camera networks, in which cameras and processing nodes may be spread over a wide geographical area, with no centralized processor and limited ability to communicate a large amount of information over long distances. This paper overviews distributed algorithms for the calibration of such camera networks- that is, the automatic estimation of each camera's position, orientation, and focal length. In particular, we discuss a decentralized method for obtaining the vision graph for a distributed camera network, in which each edge of the graph represents two cameras that image a sufficiently large part of the same environment. We next describe a distributed algorithm in which each camera performs a local, robust nonlinear optimization over the camera parameters and scene points of its vision graph neighbors in order to obtain an initial calibration estimate. We then show how a distributed inference algorithm based on belief propagation can refine the initial estimate to be both accurate and globally consistent.
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