TRAFFIC LIGHT DETECTION USING CONIC SECTION GEOMETRY
Traffic lights detection and their state recognition is a crucial task that autonomous vehicles must reliably fulfill. Despite scientific endeavors, it still is an open problem due to the variations of traffic lights and their perception in image form. Unlike previous studies, this paper investigate...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2016-06-01
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| Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/III-1/191/2016/isprs-annals-III-1-191-2016.pdf |
| Summary: | Traffic lights detection and their state recognition is a crucial task that autonomous vehicles must reliably fulfill. Despite scientific
endeavors, it still is an open problem due to the variations of traffic lights and their perception in image form. Unlike previous studies,
this paper investigates the use of inaccurate and publicly available GIS databases such as OpenStreetMap. In addition, we are the first
to exploit conic section geometry to improve the shape cue of the traffic lights in images. Conic section also enables us to estimate the
pose of the traffic lights with respect to the camera. Our approach can detect multiple traffic lights in the scene, it also is able to detect
the traffic lights in the absence of prior knowledge, and detect the traffics lights as far as 70 meters. The proposed approach has been
evaluated for different scenarios and the results show that the use of stereo cameras significantly improves the accuracy of the traffic
lights detection and pose estimation. |
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| ISSN: | 2194-9042 2194-9050 |