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Adaptive model for foreground extraction in adverse lighting conditions
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posted on 2004-01-01, 00:00 authored by Stewart GreenhillStewart Greenhill, Svetha VenkateshSvetha Venkatesh, G WestBackground elimination models are widely used in motion tracking systems. Our aim is to develop a system that performs reliably under adverse lighting conditions. In particular, this includes indoor scenes lit partly or entirely by diffuse natural light. We present a modified "median value" model in which the detection threshold adapts to global changes in illumination. The responses of several models are compared, demonstrating the effectiveness of the new model.
History
Title of book
PRICAI 2004 : trends in artificial intelligence : 8th Pacific Rim International Conference on Artificial Intelligence, Auckland, New Zealand, August 9-13, 2004 : proceedingsSeries
Lecture notes in artificial intelligence ; 3157Chapter number
85Pagination
805 - 811Publisher
Springer-VerlagPlace of publication
Berlin, GermanyPublisher DOI
ISSN
0302-9743ISBN-13
9783540228172ISBN-10
3540228179Language
engPublication classification
B1.1 Book chapterCopyright notice
2004, Springer-Verlag Berlin HeidelbergExtent
142Editor/Contributor(s)
C Zhang, H Guesgen, W YeapUsage metrics
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