@article{ref1,
title="Context-aware fusion of RGB and thermal imagery for traffic monitoring",
journal="Sensors (Basel)",
year="2016",
author="Alldieck, Thiemo and Bahnsen, Chris H. and Moeslund, Thomas B.",
volume="16",
number="11",
pages="s16111947-s16111947",
abstract="In order to enable a robust 24-h monitoring of traffic under changing environmental conditions, it is beneficial to observe the traffic scene using several sensors, preferably from different modalities. To fully benefit from multi-modal sensor output, however, one must fuse the data. This paper introduces a new approach for fusing color RGB and thermal video streams by using not only the information from the videos themselves, but also the available contextual information of a scene. The contextual information is used to judge the quality of a particular modality and guides the fusion of two parallel segmentation pipelines of the RGB and thermal video streams. The potential of the proposed context-aware fusion is demonstrated by extensive tests of quantitative and qualitative characteristics on existing and novel video datasets and benchmarked against competing approaches to multi-modal fusion.<p /> <p>Language: en</p>",
language="en",
issn="1424-8220",
doi="10.3390/s16111947",
url="http://dx.doi.org/10.3390/s16111947"
}