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2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'01) - Volume 1
A Spherical Eye from Multiple Cameras (Makes Better Models of the World)
Kauai, Hawaii
December 08-December 14
ISBN: 0-7695-1272-0
ASCII Text
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Patrick Baker, Cornelia Fermüller, Yiannis Aloimonos, Robert Pless, "A Spherical Eye from Multiple Cameras (Makes Better Models of the World)," Computer Vision and Pattern Recognition, IEEE Computer Society Conference on, vol. 1, pp. 576, 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'01) - Volume 1, 2001.
 
 
BibTex
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@article{ 10.1109/CVPR.2001.990525,
author = {Patrick Baker and Cornelia Fermüller and Yiannis Aloimonos and Robert Pless},
title = {A Spherical Eye from Multiple Cameras (Makes Better Models of the World)},
journal ={Computer Vision and Pattern Recognition, IEEE Computer Society Conference on},
volume = {1},
year = {2001},
issn = {1063-6919},
pages = {576},
doi = {http://doi.ieeecomputersociety.org/10.1109/CVPR.2001.990525},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
TI - A Spherical Eye from Multiple Cameras (Makes Better Models of the World)
SN - 1063-6919
SP
EP
A1 - Patrick Baker,
A1 - Cornelia Fermüller,
A1 - Yiannis Aloimonos,
A1 - Robert Pless,
PY - 2001
KW - null
VL - 1
JA - Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
ER -
 
Patrick Baker, University of Maryland
Cornelia Fermüller, University of Maryland
Yiannis Aloimonos, University of Maryland
Robert Pless, Washington University
This paper describes an imaging system that has been designed specifically for the purpose of recovering egomotion and structure from video. The system consists of six cameras in a network arranged so that they sample different parts of the visual sphere. This geometric configuration has provable advantages compared to small field of view cameras for the estimation of the system?s own motion and consequently the estimation of shape models from the individual cameras. The reason is that inherent ambiguities of confusion between translation and rotation disappear. We provide algorithms for the calibration of the system and the 3D motion estimation. The calibrationis based on a new geometric constraint that relates the images of lines parallel in space to the rotation between the cameras. The 3D motion estimation uses a constraint relating structure directly to image gradients.
Citation:
Patrick Baker, Cornelia Fermüller, Yiannis Aloimonos, Robert Pless, "A Spherical Eye from Multiple Cameras (Makes Better Models of the World)," cvpr, vol. 1, pp.576, 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'01) - Volume 1, 2001
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