Performance evaluation of road detection and following algorithms

Published

October 28, 2004

Author(s)

Tsai H. Hong, A Takeuchi, M Foedissch, 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

Proceedings of SPIE Optics East 2004

Conference Dates

October 25-28, 2004

Conference Location

Philadelphia, PA, USA

Conference Title

Industrial Optical Robotic Systems Technology & Applications

Pub Type

Conferences

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Keywords

false negative, false positive, groud truth, Mobility, performance evaluation, Performance Metrics, road detection, Robotics & Intelligent Systems, Vision

Citation

Hong, T. , Takeuchi, A. , Foedissch, M. and Shneier, M. (2004), Performance evaluation of road detection and following algorithms, Proceedings of SPIE Optics East 2004, Philadelphia, PA, USA, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=822556 (Accessed April 30, 2024)