Detection and Tracking the Vanishing Point on the Horizon

Young-Woo Seo
tech. report CMU-RI-TR-14-07, Robotics Institute, Carnegie Mellon University, May, 2014


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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 optimal 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 line segments, detects van- ishing points in urban scenes and, using Extended Kalman Filter (EKF), tracks 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 thousands of urban scene im- ages.

Notes

Text Reference
Young-Woo Seo, "Detection and Tracking the Vanishing Point on the Horizon," tech. report CMU-RI-TR-14-07, Robotics Institute, Carnegie Mellon University, May, 2014

BibTeX Reference
@techreport{Seo_2014_7601,
   author = "Young-Woo Seo",
   title = "Detection and Tracking the Vanishing Point on the Horizon",
   booktitle = "",
   institution = "Robotics Institute",
   month = "May",
   year = "2014",
   number= "CMU-RI-TR-14-07",
   address= "Pittsburgh, PA",
}