VANISHING POINT AIDED LANE DETECTION USING A MULTI-SENSOR SYSTEM
Abstract. Lane Detection is a critical component of an autonomous driving system that can be integrated alongside with High-definition (HD) map to improve accuracy and reliability of the system. Typically, lane detection is achieved using computer vision algorithms such as edge detection and Hough transform, deep learning-based algorithms, or motion-based algorithms to detect and track the lanes on the road. However, these approaches can contain incorrectly detected line segments with outliers. To address these issues, we proposed a vanishing point aided lane detection method that utilizes both camera and LiDAR sensors, and then employs a RANSAC-based post-processing method to remove potential outliers to improve the accuracy of the detected lanes. We evaluated this method on four datasets provided from the KITTI Benchmark Suite and achieved a total precision of 87%.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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VANISHING POINT AIDED LANE DETECTION USING A MULTI-SENSOR SYSTEM ; volume:X-1/W1-2023 ; year:2023 ; pages:635-641 ; extent:7
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences ; X-1/W1-2023 (2023), 635-641 (gesamt 7)
- Creator
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Zhang, Z.
Kang, G.
Ai, M.
El-Sheimy, N.
- DOI
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10.5194/isprs-annals-X-1-W1-2023-635-2023
- URN
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urn:nbn:de:101:1-2023120703180838215526
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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15.08.2025, 7:20 AM CEST
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Associated
- Zhang, Z.
- Kang, G.
- Ai, M.
- El-Sheimy, N.
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