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YOLinO: Generic Single Shot Polyline Detection in Real Time

Meyer, Annika; Skudlik, Philipp; Pauls, Jan-Hendrik; Stiller, Christoph


The detection of polylines is usually either bound to branchless polylines or formulated in a recurrent way, prohibiting their use in real-time systems. We propose an approach that builds upon the idea of single shot object detection. Reformulating the problem of polyline detection as a bottom-up composition of small line segments allows to detect bounded, dashed and continuous polylines with a single head. This has several major advantages over previous methods. Not only is the method at 187 fps more than suited for real-time applications with virtually any restriction on the shapes of the detected polylines. By predicting multiple line segments for each cell, even branching or crossing polylines can be detected. We evaluate our approach on three different applications for road marking, lane border and center line detection. Hereby, we demonstrate the ability to generalize to different domains as well as both implicit and explicit polyline detection tasks.

DOI: 10.1109/ICCVW54120.2021.00326
Zitationen: 6
Zugehörige Institution(en) am KIT Institut für Mess- und Regelungstechnik mit Maschinenlaboratorium (MRT)
Publikationstyp Proceedingsbeitrag
Publikationsmonat/-jahr 10.2021
Sprache Englisch
Identifikator ISBN: 978-1-66540-192-0
KITopen-ID: 1000139015
Erschienen in 2021 IEEE/CVF International Conference on Computer Vision Workshops : ICCVW 2021 : 11-17 October 2021, virtual event : proceedings. Ed.: Tamara Berg
Veranstaltung 18th IEEE/CVF International Conference on Computer Vision Workshops (ICCV 2021), Online, 11.10.2021 – 17.10.2021
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Seiten 2916-2925
Nachgewiesen in Dimensions
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