Context-Aware Fusion of RGB and Thermal Imagery for Traffic Monitoring
AbstractIn 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
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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.
Alldieck T, Bahnsen CH, Moeslund TB. Context-Aware Fusion of RGB and Thermal Imagery for Traffic Monitoring. Sensors. 2016; 16(11):1947.Chicago/Turabian Style
Alldieck, Thiemo; Bahnsen, Chris H.; Moeslund, Thomas B. 2016. "Context-Aware Fusion of RGB and Thermal Imagery for Traffic Monitoring." Sensors 16, no. 11: 1947.
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