Automated Multispectral Texture Mapping of 3D Models

Recently, thanks to the diffusion of scanning devices and the availability of powerful 3D modeling software, as well as to the improvements in the automation of the image-based modelling approach, 3D models are more and more ubiquitous in several research fields. However, 3D models obtained with these technologies are often lacking a suitable photorealistic appearance, due to low quality acquired texture, or to the complete absence of it. Moreover, it is often texturing with images different from photos, like multispetral/multimodal images (IR, Xrays, UV fluorescence) to be of specific interest. In such cases, a post-processing texture mapping is needed, and it is often achieved through manual alignment of the model and the related texture. In this work, we propose a fully automatic approach for multispectral texture mapping. The method relies on the extraction from the model geometry of a depth map, in form of an image, whose pixels maintain an exact correspondence with vertices of the 3D model; the subsequent step is the registration , between such image and the chosen texture, with a very robust registration algorithm, based on Maximixation of Mutual Information. The results presented show the effectiveness of the proposed method.