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Adaptive Randomized Algorithms for Mosaicing Systems
Frank Nielsen
Abstract:
Given a set of still images taken from a hand-held camera,
we present a fast method for mosaicing them into a single blended picture.
We design time- and memory- efficient still image mosaicing algorithms based on geometric point feature matchings that can handle both
arbitrary rotations and large zoom factors. We discuss extensions of the methodology to related problems like the recovering of the epipolar
geometry for 3d reconstruction and object recognition tasks.
Key words: registration, mosaicing, point pattern matching, bucketting
Download the PS paper here © IEICE (6873 KB, 8 pages, 9 figures).
The original publication is available at IEICE.
Bibtex entry:
@Article{n-arams-2000,
Author = {Frank Nielsen},
Title = {Adaptive Randomized Algorithms for Mosaicing Systems},
Journal = {Transactions of the Institute of Electronics, Information, and Communication
Engineers (IEICE), Information and Systems},
Volume = "E83-D",
Number = 7,
Pages = {1386-1394},
Year = 2000
}
Publication:
Frank Nielsen
Adaptive Randomized Algorithms for Mosaicing Systems,
The Institute of Electronics, Information and Communication Engineers,
IEICE Transactions on Information and Systems,
Volume E83-D, Number 7, pp. 1386-1394, July 2000.
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Last updated, 2003.