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Proceedings Paper

Performance evaluation of road detection and following systems
Author(s): Tsai H. Hong; Aya Takeuchi; Michael Foedisch; Michael O. Shneier
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Paper Abstract

We describe a methodology for evaluating algorithms to provide quantitative information about how well road detection and road following algorithms perform. The approach relies on generating a set of standard data sets annotated with ground truth. We evaluate the algorithms used to detect roads by comparing the output of the algorithms with ground truth, which we obtain by having humans annotate the data sets used to test the algorithms. Ground truth annotations are acquired from more than one person to reduce systematic errors. Results are quantified by looking at false positive and false negative regions of the image sequences when compared with the ground truth. We describe the evaluation of a number of variants of a road detection system based on neural networks.

Paper Details

Date Published: 29 December 2004
PDF: 7 pages
Proc. SPIE 5609, Mobile Robots XVII, (29 December 2004); doi: 10.1117/12.580103
Show Author Affiliations
Tsai H. Hong, National Institute of Standards and Technology (United States)
Aya Takeuchi, National Institute of Standards and Technology (United States)
Michael Foedisch, National Institute of Standards and Technology (United States)
Michael O. Shneier, National Institute of Standards and Technology (United States)


Published in SPIE Proceedings Vol. 5609:
Mobile Robots XVII
Douglas W. Gage, Editor(s)

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