| Efficient coding and multiple motions. | |
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MedLine Citation:
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PMID: 20801147 Owner: NLM Status: In-Process |
Abstract/OtherAbstract:
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Based on the principle of efficient coding, we present a theoretical framework for how to categorize the basic types of changes that can occur in a spatio-temporal signal. First, theoretical results for the problem of estimating multiple transparent motions are reviewed. Then, confidence measures for the presence of multiple motions are used to derive a basic alphabet of local signal variation that includes motion layers. To better understand and visualize this alphabet, a representation of motions in the projective plane is used. A further, practical contribution is an interactive tool that allows generating multiple motion patterns and displaying them in various apertures. In our framework, we can explain some well-known results on coherent motion and a few more complex perceptual phenomena such as the 2D-1D entrainment effect, but the focus of this paper is on the methods. Our working hypothesis is that efficient representations can be obtained by suppressing all the redundancies that arise if the visual input does not change in a particular direction, or a set of directions. Finally, we assume that human eye movements will tend to avoid the redundant parts of the visual input and report results where our framework has been used to obtain very good predictions of eye movements made on overlaid natural videos. |
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Authors:
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Erhardt Barth; Michael Dorr; Eleonora Vig; Laura Pomarjanschi; Cicero Mota |
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Publication Detail:
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Type: Journal Article Date: 2010-08-27 |
Journal Detail:
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Title: Vision research Volume: 50 ISSN: 1878-5646 ISO Abbreviation: Vision Res. Publication Date: 2010 Oct |
Date Detail:
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Created Date: 2010-10-12 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 0417402 Medline TA: Vision Res Country: England |
Other Details:
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Languages: eng Pagination: 2190-9 Citation Subset: IM |
Copyright Information:
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Copyright © 2010 Elsevier Ltd. All rights reserved. |
Affiliation:
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Institute for Neuro- and Bioinformatics, University of Lübeck, Ratzeburger Allee 160, D-23538 Lübeck, Germany. barth@inb.uni-luebeck.de |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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