License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagSemProc.10081.3
URN: urn:nbn:de:0030-drops-26285
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2010/2628/
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Belardinelli, Anna

Attending to Motion: an object-based approach

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10081.Belardinelli.2628.pdf (0.2 MB)

Abstract

Visual attention is the biological mechanism allowing to turn mere sensing
into conscious perception. In this process, object-based modulation of attention
provides a further layer between low-level space/feature-based region selection and full object recognition. In this context, motion is a very powerful feature, naturally attracting our gaze and yielding rapid and effective shape distinction.
Moving from a pixel-based account of attention to the definition of proto-objects as perceptual units labelled with a single saliency value, we present a framework for the selection of moving objects within cluttered scenes. Through segmentation of motion energy features, the system extracts coherently moving proto-objects defining them as consistently moving blobs and produces an object saliency map, by evaluating bottom-up distinctiveness of each object candidate with respect to its surroundings, in a center-surround fashion.

BibTeX - Entry

@InProceedings{belardinelli:DagSemProc.10081.3,
  author =	{Belardinelli, Anna},
  title =	{{Attending to Motion: an object-based approach}},
  booktitle =	{Cognitive Robotics},
  pages =	{1--11},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{10081},
  editor =	{Gerhard Lakemeyer and Hector J. Levesque and Fiora Pirri},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2010/2628},
  URN =		{urn:nbn:de:0030-drops-26285},
  doi =		{10.4230/DagSemProc.10081.3},
  annote =	{Keywords: Visual attention model, motion selection, saliency map}
}

Keywords: Visual attention model, motion selection, saliency map
Collection: 10081 - Cognitive Robotics
Issue Date: 2010
Date of publication: 27.10.2010

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