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Adaptive Randomized Algorithms for Mosaicing Systems

Frank Nielsen

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:

       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

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.