Detection and tracking of the vanishing point on a horizon for automotive applications

Abstract

In advanced driver assistance systems and autonomous driving vehicles, many computer vision applications rely on knowing the location of the vanishing point on a horizon. The horizontal vanishing point’s location provides important information about driving environments, such as the instantaneous driving direction of roadway, sampling regions of the drivable regions’ image features, and the search direction of moving objects. To detect the vanishing point, many existing methods work frame-by-frame. Their outputs may look desirable in that frame. Over a series of frames, however, the detected locations are inconsistent, yielding unreliable information about roadway structure. This paper presents a novel algorithm that, using the extracted line segments, detects vanishing points in urban scenes and tracks, using Extended Kalman Filter, them over frames to smooth out the trajectory of the horizontal vanishing point. The study demonstrates both the practicality of the detection method and the effectiveness of our tracking method, through experiments carried out using hundreds of urban scene images.