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.