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Proceedings Paper

Autonomous detection of indoor and outdoor signs
Author(s): Steven Holden; Magnus Snorrason; Thomas Goodsell; Mark R. Stevens
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Paper Abstract

Most goal-oriented mobile robot tasks involve navigation to one or more known locations. This is generally done using GPS coordinates and landmarks outdoors, or wall-following and fiducial marks indoors. Such approaches ignore the rich source of navigation information that is already in place for human navigation in all man-made environments: signs. A mobile robot capable of detecting and reading arbitrary signs could be tasked using directions that are intuitive to hu-mans, and it could report its location relative to intuitive landmarks (a street corner, a person's office, etc.). Such ability would not require active marking of the environment and would be functional in the absence of GPS. In this paper we present an updated version of a system we call Sign Understanding in Support of Autonomous Navigation (SUSAN). This system relies on cues common to most signs, the presence of text, vivid color, and compact shape. By not relying on templates, SUSAN can detect a wide variety of signs: traffic signs, street signs, store-name signs, building directories, room signs, etc. In this paper we focus on the text detection capability. We present results summarizing probability of detection and false alarm rate across many scenes containing signs of very different designs and in a variety of lighting conditions.

Paper Details

Date Published: 27 May 2005
PDF: 12 pages
Proc. SPIE 5804, Unmanned Ground Vehicle Technology VII, (27 May 2005); doi: 10.1117/12.604181
Show Author Affiliations
Steven Holden, Charles River Analytics (United States)
Magnus Snorrason, Charles River Analytics (United States)
Thomas Goodsell, Charles River Analytics (United States)
Mark R. Stevens, Charles River Analytics (United States)


Published in SPIE Proceedings Vol. 5804:
Unmanned Ground Vehicle Technology VII
Grant R. Gerhart; Charles M. Shoemaker; Douglas W. Gage, Editor(s)

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