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Proceedings Paper

Color characterization for landmark selection by a neural network
Author(s): Ettore Stella; F. Monte; Laura Caponetti; Arcangelo Distante
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Paper Abstract

Many of visual navigation strategies for an autonomous mobile robot are landmark based. A vehicle to determine its position needs to refer to absolute references in the environment, so landmarks are required to be invariant for rotation, translation, scale and perspective. A straightforward alternative is to be able to characterize invariantly the context where landmarks are placed. In this paper, we show as a neural network appropriately trained, is able to recognize context where landmarks are located in the scene. The early results seem to be interesting.

Paper Details

Date Published: 3 October 1995
PDF: 8 pages
Proc. SPIE 2588, Intelligent Robots and Computer Vision XIV: Algorithms, Techniques, Active Vision, and Materials Handling, (3 October 1995); doi: 10.1117/12.222670
Show Author Affiliations
Ettore Stella, Istituto Elaborazione Segnali ed Immagini (Italy)
F. Monte, Istituto Elaborazione Segnali ed Immagini (Italy)
Laura Caponetti, Univ. di Bari (Italy)
Arcangelo Distante, Istituto Elaborazione Segnali ed Immagini (Italy)


Published in SPIE Proceedings Vol. 2588:
Intelligent Robots and Computer Vision XIV: Algorithms, Techniques, Active Vision, and Materials Handling
David P. Casasent, Editor(s)

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