## 1 Introduction  
All bodies at temperature above absolute zero (0 K) emit electromagnetic radiation. If the temperature of a body has the same magnitude as the ambient temperature, then the emission is mainly relegated to the infrared (IR) range of the spectrum and can be sensed and displayed by a thermal camera as a false-color image, called a thermogram. In addition, by knowing a series of parameters such as the inspected object emissivity and the apparent reflected temperature (i.e., the ambient temperature), an approximated temperature map of the object can be computed in output. Infrared thermography is a non-invasive (non-contact and non-destructive) imaging method, which makes it a widely applicable technique. For example, it has a vast range of applications in research and industry, building and infrastructure, electrical installation inspection, microsystems engineering, but also in biology, medicine, life sciences and cultural heritage [1,2]. Like thermal imaging, 3D reconstruction techniques are nowadays widespread in many different fields and are commonly used to acquire the object geometry and to provide easy 3D documentation. They are a powerful tool to improve the identification, monitoring, conservation and restoration of objects and structures [3]. The utility of the integration is largely due to the fact that the ability to combine both temperature and geometric data together can lead to several advantages: it enhances and speeds up the interpretation of the results; it offers the possibility to select the region of interest by taking into account the geometry; it allows the easy segmentation of the 2D data from the background. One of the most important advantages, however, is that it allows one to overcome a significant limitation of 2D thermograms, namely the systematic error in the measured temperature due to the dependence of the emissivity on the viewing angle [4; 5; 6]. Several works in the literature have shown the strong potential of 3D thermal mapping (commonly known in the literature as 3D thermography). The thermal data are obtained with a thermal camera, whereas the way in which 3D data are acquired varies: a concise overview can be found in the work of [PERSON] et al. [4]. For example, in the medical field some applications of 3D thermography are the work of [PERSON] et al. [7] and the one of [PERSON] et al. [8]. In [7], the process of 3D capture relied upon stereo photogrammetry, whereas in [8] the system consisted of a high-resolution offline 3D laser scanner and a real-time low-resolution 3D scanner, both paired together with a thermal imaging camera, for human body 3D thermal model comparison and analysis. In [9], [PERSON] and [PERSON] presented \"HeatWave\", a handheld, low-cost 3D thermography system, which allows non-experts to generate detailed 3D surface temperature models for energy auditing. The core technology of this device is obtained by combining a thermal camera and an RGB-D sensor (depth sensing device coupled with an RGB camera). In several other latest applications, such as [10; 11; 12], the spatial data were obtained by using a depth camera such as the Microsoft Kinect, which has become one of the top choices for 3D thermography, because of its large versatility and the capability to be exploited to perform real-time integrations. In [13], the integration was carried out on the data acquired by two smartphones arranged in a stereo configuration and a thermal camera. In [14], a fully automatic system that generated 3D thermal models of indoor environments was presented; it consisted of a mobile platform equipped with a 3D laser scanner, an RGB camera and a thermal camera. In the cultural heritage field, spatial and multispectral data have usually been fused together for documentation reasons, historical studies, restoration plans and visualization purposes; several examples can be found in [15; 16; 17; 18; 19].