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    author = {Perrinet, Laurent U.},
    journal = {submitted},
    keywords = {assofield},
    title = {Sparse coding of natural images using a prior on edge co-occurences},
    url = {http://invibe.net/LaurentPerrinet/Publications/Perrinet15eusipco},
    year = {2015}
AUTHOR="Laurent Perrinet and James Bednar",
TITLE="Sparse Coding Of Natural Images Using A Prior On Edge {Co-Occurences}",
BOOKTITLE="European Signal Processing Conference 2015 (EUSIPCO 2015)",
ADDRESS="Nice, France",
KEYWORDS="sparse coding; natural scene statistics; sparselets; lateral connections;
association field",
ABSTRACT={Oriented edges in images of natural scenes tend to be aligned in co-linear
or co-circular arrangements, with lines and smooth curves more common than
other possible arrangements of edges (the "good continuation law" of
Gestalt psychology). The visual system appears to take advantage of this
prior knowledge about natural images, with human contour detection and
grouping performance well predicted by such an "association field"
between edge elements. Geisler et al (2001) have estimated this prior
information available to the visual system by extracting contours from a
database of natural images, and showed that these statistics could predict
behavioral data from humans in a line completion task. In this paper, we
show that an association field of this type can be used for the sparse
representation of natural images.}
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TagYear15 TagBrainScales TagPublicationsInPreparation TagPublicationsInPreparation TagYear15 TagBrainScales TagPublicationsInPreparation

Sparse coding of natural images using a prior on edge co-occurences


  • Laurent Perrinet, James Bednar. Sparse Coding Of Natural Images Using A Prior On Edge Co-Occurences. In European Signal Processing Conference 2015 (EUSIPCO 2015), Nice, France, 2015 abstract.
  • Strange line [representation of natural images.}] found

All material (c) L. Perrinet. Please check the copyright notice.

This work was supported by European Union project Number FP7-269921, "BrainScales".
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