"Ecce Homo" by Antonello da Messina, from non-invasive investigations to data fusion and dissemination.

Scientific investigations of artworks are crucial in terms of preservation since they provide a measurable evaluation of the materials and the state of conservation. This is the case of Antonello da Messina's painting "Ecce Homo": its delicate state of conservation, with the need for constant monitoring, required a broad and in-depth diagnostic campaign to support the restorers. The project was carried out entirely in situ using non-invasive cutting-edge techniques and proposes a multimodal and data-centric approach, integrating 3D and 2D methodologies. The surface irregularities and the support were analysed with a structured-light 3D scanner and X-ray tomography. The painting materials were investigated with X-ray fluorescence scanning (MA-XRF) and reflectance hyperspectral imaging (HSI). Primarily, the data were jointly used for a scientific scope and provided new knowledge of the painting in terms of materials and painting techniques. In addition, two web-based interactive platforms were developed: one to provide restorers and experts with a new perspective of the hidden geometries of the painting, and the other targeted at the general public for dissemination purposes. The results of the Ecce Homo scientific analysis were exhibited, using a touch-screen interface, and developed for different user levels, from adults to kids.

Presentation of 3D Scenes Through Video Example.

Using synthetic videos to present a 3D scene is a common requirement for architects, designers, engineers or Cultural Heritage professionals however it is usually time consuming and, in order to obtain high quality results, the support of a film maker/computer animation expert is necessary. We introduce an alternative approach that takes the 3D scene of interest and an example video as input, and automatically produces a video of the input scene that resembles the given video example. In other words, our algorithm allows the user to "replicate" an existing video, on a different 3D scene. We build on the intuition that a video sequence of a static environment is strongly characterized by its optical flow, or, in other words, that two videos are similar if their optical flows are similar. We therefore recast the problem as producing a video of the input scene whose optical flow is similar to the optical flow of the input video. Our intuition is supported by a user-study specifically designed to verify this statement. We have successfully tested our approach on several scenes and input videos, some of which are reported in the accompanying material of this paper.

Relative Scale Estimation and 3D Registration of Multi-Modal Geometry Using Growing Least Squares.

The advent of low cost scanning devices and the improvement of multi-view stereo techniques have made the acquisition of 3D geometry ubiquitous. Data gathered from different devices, however, result in large variations in detail, scale, and coverage. Registration of such data is essential before visualizing, comparing and archiving them. However, state-of-the-art methods for geometry registration cannot be directly applied due to intrinsic differences between the models, e.g., sampling, scale, noise. In this paper we present a method for the automatic registration of multi-modal geometric data, i.e., acquired by devices with different properties (e.g., resolution, noise, data scaling). The method uses a descriptor based on Growing Least Squares, and is robust to noise, variation in sampling density, details, and enables scale-invariant matching. It allows not only the measurement of the similarity between the geometry surrounding two points, but also the estimation of their relative scale. As it is computed locally, it can be used to analyze large point clouds composed of millions of points. We implemented our approach in two registration procedures (assisted and automatic) and applied them successfully on a number of synthetic and real cases. We show that using our method, multi-modal models can be automatically registered, regardless of their differences in noise, detail, scale, and unknown relative coverage.

PhotoCloud: Interactive remote exploration of joint 2D and 3D datasets.

PhotoCloud is a real-time client-server system for interactive visualization and exploration of large datasets comprising thousands of calibrated 2D photographs of a scene and a complex 3D description of the scene. The system isn't tailored to any specific data acquisition process; it aims at generality and flexibility. PhotoCloud achieves scalability through a multiresolution dynamic hierarchical representation of the data, which is remotely stored and accessed by the client through an efficient cache system. The system includes a compact image browser and a multiresolution model renderer. PhotoCloud employs iconic visualization of the images in the 3D space and projects images onto the 3D scene on the fly. Users can navigate the 2D and 3D spaces with smooth, integrated, seamless transitions between them. A study with differently skilled users confirms PhotoCloud's effectiveness and communication power. The Web extras at http://www.youtube.com/playlist?list=PLHJB2bhmgB7cmYD0ST9CEDMRv1JlX4xPH are videos demonstrating PhotoCloud, a real-time client-server system for interactive exploration of large datasets comprising 2D photos and 3D models.

Efficient and flexible sampling with blue noise properties of triangular meshes.

This paper deals with the problem of taking random samples over the surface of a 3D mesh describing and evaluating efficient algorithms for generating different distributions. We discuss first the problem of generating a Monte Carlo distribution in an efficient and practical way avoiding common pitfalls. Then, we propose Constrained Poisson-disk sampling, a new Poisson-disk sampling scheme for polygonal meshes which can be easily tweaked in order to generate customized set of points such as importance sampling or distributions with generic geometric constraints. In particular, two algorithms based on this approach are presented. An in-depth analysis of the frequency characterization and performance of the proposed algorithms are also presented and discussed.

Flow-based local optimization for image-to-geometry projection.

The projection of a photographic data set on a 3D model is a robust and widely applicable way to acquire appearance information of an object. The first step of this procedure is the alignment of the images on the 3D model. While any reconstruction pipeline aims at avoiding misregistration by improving camera calibrations and geometry, in practice a perfect alignment cannot always be reached. Depending on the way multiple camera images are fused on the object surface, remaining misregistrations show up either as ghosting or as discontinuities at transitions from one camera view to another. In this paper we propose a method, based on the computation of Optical Flow between overlapping images, to correct the local misalignment by determining the necessary displacement. The goal is to correct the symptoms of misregistration, instead of searching for a globally consistent mapping, which might not exist. The method scales up well with the size of the data set (both photographic and geometric) and is quite independent of the characteristics of the 3D model (topology cleanliness, parametrization, density). The method is robust and can handle real world cases that have different characteristics: low level geometric details and images that lack enough features for global optimization or manual methods. It can be applied to different mapping strategies, such as texture or per-vertex attribute encoding.

A parallel architecture for interactively rendering scattering and refraction effects.

A new method for interactive rendering of complex lighting effects combines two algorithms. The first performs accurate ray tracing in heterogeneous refractive media to compute high-frequency phenomena. The second applies lattice-Boltzmann lighting to account for low-frequency multiple-scattering effects. The two algorithms execute in parallel on modern graphics hardware. This article includes a video animation of the authors' real-time algorithm rendering a variety of scenes.

OCME: Out-of-Core Mesh Editing made practical.

OCME (Out-of-Core Mesh Editing) comprises a novel data structure and related algorithms for out-of-core editing of large meshes. Triangles are inserted in a multigrid on the basis of their size in average constant time. OCME maintains no explicit hierarchy, so inserting, modifying, or deleting data doesn't require costly refitting.

An interactive local flattening operator to support digital investigations on artwork surfaces.

Analyzing either high-frequency shape detail or any other 2D fields (scalar or vector) embedded over a 3D geometry is a complex task, since detaching the detail from the overall shape can be tricky. An alternative approach is to move to the 2D space, resolving shape reasoning to easier image processing techniques. In this paper we propose a novel framework for the analysis of 2D information distributed over 3D geometry, based on a locally smooth parametrization technique that allows us to treat local 3D data in terms of image content. The proposed approach has been implemented as a sketch-based system that allows to design with a few gestures a set of (possibly overlapping) parameterizations of rectangular portions of the surface. We demonstrate that, due to the locality of the parametrization, the distortion is under an acceptable threshold, while discontinuities can be avoided since the parametrized geometry is always homeomorphic to a disk. We show the effectiveness of the proposed technique to solve specific Cultural Heritage (CH) tasks: the analysis of chisel marks over the surface of a unfinished sculpture and the local comparison of multiple photographs mapped over the surface of an artwork. For this very difficult task, we believe that our framework and the corresponding tool are the first steps toward a computer-based shape reasoning system, able to support CH scholars with a medium they are more used to.

Solid-texture synthesis: a survey.

Solid textures are an efficient way to compactly represent 3D objects' external and internal appearance, providing practical advantages over classic 2D texturing. Two main methods exist for synthesizing solid textures. Procedural methods obtain colors through functions that algorithmically encode the texture's appearance and structural properties. Example-based methods capture and replicate the appearance as described by a set of input exemplars. These methods can also be classified as boundary independent or boundary dependent. For boundary-independent methods, the shape of the object to be textured is irrelevant, and texture information can be freely generated for each point in the space. Boundary-dependent methods conform the synthesis process to the object's actual shape so that they can exploit this information to orient and guide texture generation. This article reviews the different methodologies' strengths and weaknesses, the classes of appearances they can successfully synthesize, and failure cases. In particular, it focuses on boundary-independent methods' advantages and drawbacks compared to boundary-dependent methods.

Selective refinement queries for volume visualization of unstructured tetrahedral meshes.

In this paper, we address the problem of the efficient visualization of large irregular volume data sets by exploiting a multiresolution model based on tetrahedral meshes. Multiresolution models, also called Level-Of-Detail (LOD) models, allow encoding the whole data set at a virtually continuous range of different resolutions. We have identified a set of queries for extracting meshes at variable resolution from a multiresolution model, based on field values, domain location, or opacity of the transfer function. Such queries allow trading off between resolution and speed in visualization. We define a new compact data structure for encoding a multiresolution tetrahedral mesh built through edge collapses to support selective refinement efficiently and show that such a structure has a storage cost from 3 to 5.5 times lower than standard data structures used for tetrahedral meshes. The data structures and variable resolution queries have been implemented together with state-of-the art visualization techniques in a system for the interactive visualization of three-dimensional scalar fields defined on tetrahedral meshes. Experimental results show that selective refinement queries can support interactive visualization of large data sets.