@inproceedings{9ccc4a95143f4b9a938ceab73f599efc,
title = "Detecting Road Users at Intersections Through Changing Weather Using RGB-Thermal Videos",
abstract = "This paper compares the performance of a watch-dog sys- tem that detects road user actions in urban intersections to a KLT- based tracking system used in traffic surveillance. The two approaches are evaluated on 16 hours of video data captured by RGB and ther- mal cameras under challenging light and weather conditions. On this dataset, the detection performance of right turning vehicles, left turn- ing vehicles, and straight going cyclists are evaluated. Results from both systems show good performance when detecting turning vehicles with a precision of 0.90 and above depending on environmental conditions. The detection performance of cyclists shows that further work on both systems is needed in order to obtain acceptable recall rates.",
author = "Chris Bahnsen and Moeslund, {Thomas B.}",
year = "2015",
month = dec,
day = "23",
doi = "10.1007/978-3-319-27857-5_66",
language = "English",
isbn = "978-3-319-27856-8",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "741--751",
booktitle = "Advances in Visual Computing",
address = "Germany",
note = "ISVC 2015 ; Conference date: 14-12-2015 Through 16-12-2015",
}