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Sensors 2016, 16(11), 1947; doi:10.3390/s16111947

Context-Aware Fusion of RGB and Thermal Imagery for Traffic Monitoring

Visual Analysis of People Lab, Aalborg University, 9000 Aalborg, Denmark
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Author to whom correspondence should be addressed.
Academic Editors: Xue-Bo Jin, Feng-Bao Yang, Shuli Sun and Hong Wei
Received: 29 July 2016 / Revised: 8 November 2016 / Accepted: 14 November 2016 / Published: 18 November 2016
(This article belongs to the Special Issue Advances in Multi-Sensor Information Fusion: Theory and Applications)
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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. View Full-Text
Keywords: context-aware fusion; traffic surveillance; segmentation context-aware fusion; traffic surveillance; segmentation
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Alldieck, T.; Bahnsen, C.H.; Moeslund, T.B. Context-Aware Fusion of RGB and Thermal Imagery for Traffic Monitoring. Sensors 2016, 16, 1947.

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