Abstract In this paper, we discuss the requirements and technical challenges within the EHEM project, Enhancement of Heritage Experiences: The Middle Ages, an ongoing research program for the acquisition, analysis, documentation, interpretation, digital restoration, and communication of medieval artistic heritage. The project involves multidisciplinary teams comprising art historians and visual computing experts. Despite the vast literature on digital 3D models in support of Cultural Heritage, the field is so rich and diverse that specific projects often imply distinct, unique requirements which often challenge the computational technologies and suggest new research opportunities. As good representatives of such diversity, we describe the three monuments that serve as test cases for the project, all of them with a rich history of architecture and paintings. We discuss the art historians’ view of how digital models can support their research, the expertise and technological solutions adopted so far, as well as the technical challenges in multiple areas spanning geometry and appearance acquisition, color analysis and digital restitution, as well as the representation of the profound transformations due to the alterations suffered over the centuries.

Digital color restitution aims to digitally restore the original colors of a painting. Existing image editing applications can be used for this purpose, but they require a select-and-edit workflow and thus they do not scale well to large collections of paintings or different regions of the same painting. To address this issue, we propose an automated workflow that requires only a few representative source colors and associated target colors as input from art historians. The system then creates a control grid to model a deformation of the CIELAB color space. Such deformation can be applied to arbitrary images of the same painting. The proposed approach is suitable for restituting the color of images from a large photographic campaign, as well as for the textures of 3D reconstructions of a monument. We demonstrate the benefits of our method on a collection of mural paintings from a medieval monument.

High-end Terrestrial Lidar Scanners are often equipped with RGB cameras that are used to colorize the point samples. Some of these scanners produce panoramic HDR images by encompassing the information of multiple pictures with different exposures. Unfortunately, exported RGB color values are not in an absolute color space, and thus point samples with similar reflectivity values might exhibit strong color differences depending on the scan the sample comes from. These color differences produce severe visual artifacts if, as usual, multiple point clouds colorized independently are combined into a single point cloud. In this paper we propose an automatic algorithm to minimize color differences among a collection of registered scans. The basic idea is to find correspondences between pairs of scans, i.e. surface patches that have been captured by both scans. If the patches meet certain requirements, their colors should match in both scans. We build a graph from such pair-wise correspondences, and solve for the gain compensation factors that better uniformize color across scans. The resulting panoramas can be used to colorize the point clouds consistently. We discuss the characterization of good candidate matches, and how to find such correspondences directly on the panorama images instead of in 3D space. We have tested this approach to uniformize color across scans acquired with a Leica RTC360 scanner, with very good results.

Weathering effects are ubiquitous phenomena in cities. Buildings age and deteriorate over time as they interact with the environment. Pollution accumulating on facades is a particularly visible consequence of this. Even though relevant work has been done to produce impressive images of virtual urban environments including weathering effects, so far, no technique using a global approach has been proposed to deal with weathering effects. Here, we propose a technique based on a fast physically-inspired approach, that focuses on modeling the changes in appearance due to pollution soiling on an urban scale. We consider pollution effects to depend on three main factors: wind, rain and sun exposure, and we take into account three intervening steps: deposition, reaction and washing. Using a low-cost pre-computation, we evaluate the pollution distribution throughout the city. Based on this and the use of screen-space operators, our method results in an efficient approach able to generate realistic images of urban scenes by combining the intervening factors at interactive rates. In addition, the pre-computation demands a reduced amount of memory to store the resulting pollution map and, as it is independent from scene complexity, it can suit large and complex models by adapting the map resolution.

Abstract In urban design, estimating solar exposure on complex city models is crucial but existing solutions typically focus on simplified building models and are too demanding in terms of memory and computational time. In this paper, we propose an interactive technique that estimates solar exposure on detailed urban scenes. Given a directional exposure map computed over a given time period, we estimate the sky visibility factor that serves to evaluate the final exposure at each visible point. This is done using a screen‐space method based on a two‐scale approach, which is geometry independent and has low storage costs. Our method performs at interactive rates and is designer‐oriented. The proposed technique is relevant in architecture and sustainable building design as it provides tools to estimate the energy performance of buildings as well as weathering effects in urban environments.