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Published Articles >> Table of Contents >> Abstract
Second International Symposium on 3D Data Processing, Visualization and Transmission (3DPVT'04)
pp. 733-740
Multi-Camera Reconstruction based on Surface Normal Estimation and Best Viewpoint Selection
Xenophon Zabulis, University of Pennsylvania, Philadelphia
Kostas Daniilidis, University of Pennsylvania, Philadelphia
Full Article Text:
  
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TDPVT.2004.1335388
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| Abstract |
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In this paper, we present a new algorithm for reconstructing
an environment from images recorded by multiple
calibrated cameras. Multiple camera systems challenge
traditional stereo algorithms in many issues including view
registration, selection of commonly visible image parts for
matching, and the fact that surfaces are imaged differently
from different viewpoints and poses. On the other hand,
multiple cameras have the advantage of revealing surfaces
at occluding contours and covering wide areas.
The presented algorithm makes no assumption on camera
loci and outputs an occupancy voxel grid, with occupied
voxels being accompanied by a surface normal. It is
correlation-based, however, outperforms the conventional
correlation-based approach in reconstruction quality. It
is highly parallelizable, and most importantly, is robust
against artifacts due to camera registration errors that are
typically encountered when using multiple cameras.
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 Additional Information
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Citation:
Xenophon Zabulis, Kostas Daniilidis,
"Multi-Camera Reconstruction based on Surface Normal Estimation and Best Viewpoint Selection,"
3dpvt,
pp. 733-740,
Second International Symposium on 3D Data Processing, Visualization and Transmission (3DPVT'04),
2004
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