A Vision System for Detection and Tracking of Stop-Lines

Young-Woo Seo
tech. report CMU-RI-TR-14-09, Robotics Institute, Carnegie Mellon University, June, 2014


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Abstract
This paper presents a computer vision algorithm that detects, by analyzing lane- marking detection results, stop-lines and tracks, using an unscented Kalman filter, the detected stop-line over time. To detect lateral and longitudinal lane-markings, our method applies a spatial filter emphasizing the intensity contrast between lane- marking pixels and their neighboring pixels. We then examine the detected lane- markings to identify perpendicular, geometry layouts between longitudinal and lat- eral lane-markings for stop-line detection. To provide reliable stop-line recognition, we developed an unscented Kalman filter to track the detected stop-line over frames. Through the testings with real-world, busy urban street videos, our method demon- strated promising results, in terms of the accuracy of the initial detection accuracy and the reliability of the tracking.

Notes

Text Reference
Young-Woo Seo, "A Vision System for Detection and Tracking of Stop-Lines," tech. report CMU-RI-TR-14-09, Robotics Institute, Carnegie Mellon University, June, 2014

BibTeX Reference
@techreport{Seo_2014_7602,
   author = "Young-Woo Seo",
   title = "A Vision System for Detection and Tracking of Stop-Lines",
   booktitle = "",
   institution = "Robotics Institute",
   month = "June",
   year = "2014",
   number= "CMU-RI-TR-14-09",
   address= "Pittsburgh, PA",
}