3 October 1995 Color characterization for landmark selection by a neural network
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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


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