YOLinO: Generic Single Shot Polyline Detection in Real Time
This enables real-time polyline detection for applications like road marking and lane detection, with incremental improvements in speed and flexibility.
The paper tackles the problem of polyline detection in real-time systems by proposing a single-shot approach that detects bounded, dashed, and continuous polylines, achieving 187 fps and handling branching or crossing shapes.
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.