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| Publication ID | 359 |
| Title | An Integrated, Robust Approach to Lane Marking Detection and Lane Tracking |
| Submitted on | 2010-2-9 |
| Published in | IEEE Intelligent Vehicles Symposium, University of Parma, Italy |
| Date of Publication | 2004-06-00 |
| Author | Joel McCall; Mohan Trivedi; |
| Project | |
| Type | Conference or Journal Paper |
| Subject group | Engineering and Transportation Information Dissemination |
| Abstract | Lane Detection is a difficult problem because of the varying road conditions that one can encounter while driving. In this paper, we propose a method for lane detection using steerable filters. Steerable filters provide robustness to lighting changes and shadows and perform well in picking out both circular reflector road markings as well as the painted line road markings. The filter results are then processed to eliminate outliers based on the expected road geometry and used to update a road and vehicular model along with data taken internally from the vehicle. Results are shown for a 9000-frame image sequence that include varying lane markings, lighting conditions, showing, and occlusion by other vehicles. |
| Fulltext source | PDF (pdf) |
| Document Managed by | rescue@ics.uci.edu |
This material is based upon work supported by the National Science Foundation under Award Numbers 0331707 and 0331690. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation
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