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Proceedings Paper

Adaptive learning applied to terrain recognition
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Paper Abstract

This paper presents an exploration of methods for estimating terrain trafficability from visual appearance. Two different sets of data are used. The first set is extracted from video sequences and has a small number of different terrains. A fuzzy c-means clustering algorithm is used to predict terrain type. The second set is derived from high-resolution still images and has a large variety of terrains. A decision tree algorithm is used to provide a subjective assessment of trafficability. A variety of local features are explored, based on color and texture, as input to the learning algorithms.

Paper Details

Date Published: 16 April 2008
PDF: 10 pages
Proc. SPIE 6962, Unmanned Systems Technology X, 69620H (16 April 2008); doi: 10.1117/12.777289
Show Author Affiliations
Robert E. Karlsen, U.S. Army TARDEC (United States)
Gary Witus, Turing Associates, Inc. (United States)


Published in SPIE Proceedings Vol. 6962:
Unmanned Systems Technology X
Grant R. Gerhart; Douglas W. Gage; Charles M. Shoemaker, Editor(s)

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