3 October 1995 Color characterization for landmark selection by a neural network
Author Affiliations +
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.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ettore Stella, Ettore Stella, F. Monte, F. Monte, Laura Caponetti, Laura Caponetti, Arcangelo Distante, Arcangelo Distante, } "Color characterization for landmark selection by a neural network", Proc. SPIE 2588, Intelligent Robots and Computer Vision XIV: Algorithms, Techniques, Active Vision, and Materials Handling, (3 October 1995); doi: 10.1117/12.222670; https://doi.org/10.1117/12.222670
PROCEEDINGS
8 PAGES


SHARE
RELATED CONTENT

A self-learning machine vision system
Proceedings of SPIE (March 04 2004)
Door detection in images based on learning by components
Proceedings of SPIE (October 05 2001)
Pyramid nets for computer vision
Proceedings of SPIE (March 01 1991)

Back to Top