Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Performance Evaluation of Road Detection and Following Systems

Published

Author(s)

Tsai Hong Hong, A Takeucki, Mike Foedisch, Michael O. Shneier

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.
Proceedings Title
Mobile Robots 2004 | 17th | Proceedings of SPIE--the International Society for Optical Engineering | SPIE
Volume
5609
Conference Dates
October 26-28, 2004
Conference Title
Proceedings of SPIE--the International Society for Optical Engineering

Keywords

false negative, false positive, ground truth, performance evaluation, road detection, road following

Citation

, T. , Takeucki, A. , Foedisch, M. and Shneier, M. (2004), Performance Evaluation of Road Detection and Following Systems, Mobile Robots 2004 | 17th | Proceedings of SPIE--the International Society for Optical Engineering | SPIE, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=823525 (Accessed April 15, 2024)
Created October 1, 2004, Updated February 17, 2017