Johansen, A.S.; Nasrollahi, K.; Escalera, S.; Moeslund, T.B. Who Cares about the Weather? Inferring Weather Conditions for Weather-Aware Object Detection in Thermal Images. Appl. Sci.2023, 13, 10295.
Johansen, A.S.; Nasrollahi, K.; Escalera, S.; Moeslund, T.B. Who Cares about the Weather? Inferring Weather Conditions for Weather-Aware Object Detection in Thermal Images. Appl. Sci. 2023, 13, 10295.
Johansen, A.S.; Nasrollahi, K.; Escalera, S.; Moeslund, T.B. Who Cares about the Weather? Inferring Weather Conditions for Weather-Aware Object Detection in Thermal Images. Appl. Sci.2023, 13, 10295.
Johansen, A.S.; Nasrollahi, K.; Escalera, S.; Moeslund, T.B. Who Cares about the Weather? Inferring Weather Conditions for Weather-Aware Object Detection in Thermal Images. Appl. Sci. 2023, 13, 10295.
Abstract
Deployments of real-world object-detection systems often experience a degradation in performance over time due to concept drift. Systems that leverage thermal cameras are especially susceptible because the respective thermal signatures of objects and their surroundings are highly sensitive to environmental changes. In this study, a conditioning method is investigated. The method aims to guide the training loop of thermal object detection systems by leveraging an auxiliary branch to predict the weather, while directly or indirectly conditioning the baseline detection system. Leveraging such an approach to train detection networks does not necessarily improve the performance of native architectures, however, it can be observed that conditioned networks manage to extract a signal from thermal images that guides the network to detect objects that baseline models miss. As the extracted signal appears to be quite noisy and very challenging to regress accurately, further work is needed to identify an ideal optimization vector.
Computer Science and Mathematics, Computer Vision and Graphics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
