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Efficient Ego Lane Detection for Various LaneTypes

Peter, Rebekka Charlotte; Song, Yuduo; Lauer, Martin ORCID iD icon

Abstract (englisch):

In this work, we present an ego lane detector de-signed for the use in automotive vision systems for personallight electric vehicles like electric bicycles, tricycles or scoot-ers. The approach is based on a combination of gradient-based line detection, color-based segmentation and geomet-rical rules, making the ego lane detector fast, but also robustto different scenes, including curves. Qualitative evaluationon over fifty traffic scenes show that the lane detector is ableto find a suitable approximation of the road area with an IoUof 75.71%.

Verlagsausgabe §
DOI: 10.5445/IR/1000129397
Veröffentlicht am 05.02.2021
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Mess- und Regelungstechnik mit Maschinenlaboratorium (MRT)
Publikationstyp Proceedingsbeitrag
Publikationsmonat/-jahr 11.2020
Sprache Englisch
Identifikator ISBN: 978-3-7315-1053-6
KITopen-ID: 1000129397
Erschienen in Forum Bildverarbeitung 2020. Ed.: T. Längle ; M. Heizmann
Verlag KIT Scientific Publishing
Seiten 413-424
Schlagwörter Ego lane detection, color-based segmentation, vanishing point detection
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