Title :
Robust Traffic State Estimation on Smart Cameras
Author :
Pletzer, Felix ; Tusch, Roland ; Böszörmenyi, Laszlo ; Rinner, Bernhard
Author_Institution :
Lakeside Labs., Alpen-Adria-Univ. Klagenfurt, Klagenfurt, Austria
Abstract :
This paper presents a novel method for video-based traffic state detection on motorways performed on smart cameras. Camera calibration parameters are obtained from the known length of lane markings. Mean traffic speed is estimated from Kanade-Lucas-Tomasi (KLT) optical flow method using a robust outlier detection. Traffic density is estimated using a robust statistical counting method. Our method has been implemented on an embedded smart camera and evaluated under different road and illumination conditions. It achieves a detection rate of more than 95% for stationary traffic.
Keywords :
cameras; image sequences; intelligent sensors; state estimation; statistical analysis; traffic engineering computing; video signal processing; KLT optical flow method; camera calibration parameters; detection rate; embedded smart camera; illumination conditions; kanade-lucas-tomasi optical flow method; lane markings; mean traffic speed; motorways; road conditions; robust outlier detection; robust traffic state estimation; stationary traffic; video-based traffic state detection; Cameras; Estimation; Roads; Smart cameras; Streaming media; Vectors; Vehicles; embedded computer vision; smart cameras; traffic state detection;
Conference_Titel :
Advanced Video and Signal-Based Surveillance (AVSS), 2012 IEEE Ninth International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-2499-1
DOI :
10.1109/AVSS.2012.63