TY - GEN
T1 - Visualization of temperature change using RGB-D camera and thermal camera
AU - Nakagawa, Wataru
AU - Matsumoto, Kazuki
AU - de Sorbier, Francois
AU - Sugimoto, Maki
AU - Saito, Hideo
AU - Senda, Shuji
AU - Shibata, Takashi
AU - Iketani, Akihiko
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - In this paper, we present a system for visualizing temperature changes in a scene using an RGB-D camera coupled with a thermal camera. This system has applications in the context of maintenance of power equipments. We propose a two-stage approach made of with an offline and an online phases. During the first stage, after the calibration, we generate a 3D reconstruction of the scene with the color and the thermal data. We then apply the Viewpoint Generative Learning (VGL) method on the colored 3D model for creating a database of descriptors obtained from features robust to strong viewpoint changes. During the second online phase we compare the descriptors extracted from the current view against the ones in the database for estimating the pose of the camera. In this situation, we can display the current thermal data and compare it with the data saved during the offline phase.
AB - In this paper, we present a system for visualizing temperature changes in a scene using an RGB-D camera coupled with a thermal camera. This system has applications in the context of maintenance of power equipments. We propose a two-stage approach made of with an offline and an online phases. During the first stage, after the calibration, we generate a 3D reconstruction of the scene with the color and the thermal data. We then apply the Viewpoint Generative Learning (VGL) method on the colored 3D model for creating a database of descriptors obtained from features robust to strong viewpoint changes. During the second online phase we compare the descriptors extracted from the current view against the ones in the database for estimating the pose of the camera. In this situation, we can display the current thermal data and compare it with the data saved during the offline phase.
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U2 - 10.1007/978-3-319-16178-5_27
DO - 10.1007/978-3-319-16178-5_27
M3 - Conference contribution
AN - SCOPUS:84925337409
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 386
EP - 400
BT - Computer Vision - ECCV 2014 Workshops, Proceedings
A2 - Bronstein, Michael M.
A2 - Rother, Carsten
A2 - Agapito, Lourdes
PB - Springer Verlag
T2 - 13th European Conference on Computer Vision, ECCV 2014
Y2 - 6 September 2014 through 12 September 2014
ER -