This paper describes an environment to automatically or semi-automatically compute the precise mapping between a set of 2D images and a triangulated 3D model built from high-resolution 3D range data. This environment is part of our Atelier3D framework for the modeling, visualization and analysis of large sensor-based datasets. This work was done to initially support three cultural heritage application projects: the modeling of the Grotta dei Cervi in Italy, of the Erechtheion in Athens, Greece, and of Leonardo's Mona Lisa. The proposed method combines image-based registration, feature matching, robust estimation techniques and advanced multi-resolution rendering with a powerful user interface.

Three-dimensional digital modeling of Heritage works of art through optical scanners, has been demonstrated in recent years with results of exceptional interest. However, the routine application of three-dimensional (3-D) modeling to Heritage conservation still requires the systematic investigation of a number of technical problems. In this paper, the acquisition process of the 3-D digital model of the Maddalena by Donatello, a wooden statue representing one of the major masterpieces of the Italian Renaissance which was swept away by the Florence flood of 1966 and successively restored, is described. The paper reports all the steps of the acquisition procedure, from the project planning to the solution of the various problems due to range camera calibration and to material non optically cooperative. Since the scientific focus is centered on the 3-D model overall dimensional accuracy, a methodology for its quality control is described. Such control has demonstrated how, in some situations, the ICP-based alignment can lead to incorrect results. To circumvent this difficulty we propose an alignment technique based on the fusion of ICP with close-range digital photogrammetry and a non-invasive procedure in order to generate a final accurate model. In the end detailed results are presented, demonstrating the improvement of the final model, and how the proposed sensor fusion ensure a pre-specified level of accuracy.

Abstract The National Research Council of Canada (NRC) has developed and patented three high‐resolution 3D imaging systems and processing algorithms which have been applied to a wide range of museum and heritage recording applications. The systems have been designed for different imaging applications and, in collaboration with a number of national and international museums and cultural agencies, have been used to scan a wide variety of objects and sites. The objective of this paper is to present a summary of the 3D technology and examples of its heritage applications. Copyright © 2003 John Wiley & Sons, Ltd.

The generation of three-dimensional (3-D) digital models produced by optical technologies in some cases involves metric errors. This happens when small high-resolution 3-D images are assembled together in order to model a large object. In some applications, as for example 3-D modeling of Cultural Heritage, the problem of metric accuracy is a major issue and no methods are currently available for enhancing it. The authors present a procedure by which the metric reliability of the 3-D model, obtained through iterative alignments of many range maps, can be guaranteed to a known acceptable level. The goal is the integration of the 3-D range camera system with a close range digital photogrammetry technique. The basic idea is to generate a global coordinate system determined by the digital photogrammetric procedure, measuring the spatial coordinates of optical targets placed around the object to be modeled. Such coordinates, set as reference points, allow the proper rigid motion of few key range maps, including a portion of the targets, in the global reference system defined by photogrammetry. The other 3-D images are normally aligned around these locked images with usual iterative algorithms. Experimental results on an anthropomorphic test object, comparing the conventional and the proposed alignment method, are finally reported.

3D optical scanning technologies for measuring tridimensional shapes of sculptures have emerged in the last few years as the most promising methods for digital analysis and preservation of cultural heritage. This paper presents the work leading to the generation of the digital 3D model of Donatello's Maddalena, kept in the museum of the Opera del Duomo in Florence. The acquisitions have been taken with a system based on fringe projection. The metric reliability of Maddalena's tridimensional model, obtained through iterative alignments of single 3D acquisitions, has been also verified through a well established technique such as photogrammetry. A set of point-to-point distances evaluated with both methods has been compared and discussed in order to estimate the overall accuracy of the final model.

Discusses the progress and the evolution of the development of range sensing techniques at the NRC laboratories. Essentially a 3D imaging project at the beginning, it has evolved to a new media project which requires the development of new tools for 3D modeling, editing, database searching and visualization. Generic applications related to documentation, inspection, target tracking and visual communication will be discussed.

A method of estimating range flow (space displacement vector field) on nonrigid as well as rigid objects from a sequence of range images is described. This method can directly estimate the deformable motion parameters by solving a system of linear equations that are obtained from substituting a linear transformation of nonrigid objects expressed by the Jacobian matrix into motion constraints based on an extension of the conventional scheme used in intensity image sequences. The range flow is directly computed by substituting these estimated motion parameters into the linear transformation. The algorithm is supported by experimental estimations of range flow on a sheet of paper, a piece of cloth, human skin, and a rubber balloon being inflated, using real range image sequences acquired by a video rate range camera.>

Introduces a new method for the calibration of a range camera based on active triangulation. The technique is based on a model derived from the geometry of the synchronized scanner. From known positions of a calibration bar, a logistic equation is fitted with values of spot positions read from a linear position detector at a number of angular positions of a scanning mirror. Furthermore, with an approximate form of the general equations describing the geometry, a series of design guidelines are derived to help a designer conduct a preliminary study of a particular range camera. Experimental results demonstrating the technique are found to compare favorably with theoretical predictions.>

A method is described for estimating range flow (space displacement vector field) on a nonrigid object as well as a rigid object from a sequence of range images. The method can directly estimate the deformable motion parameters by solving a system of linear equations which are obtained by substituting a linear transformation of a nonrigid object expressed by a Jacobian matrix into motion constraints based on an extension of the conventional scheme used in intensity image sequences, and the range flow is obtained from the motion parameters and linear transformation. The algorithm is supported by experiments of motion estimation of a sheet of paper, a piece of cloth, the movement of human skin, and the motion of a rubber balloon being inflated using real range image sequences acquired by a video rate range finder. Furthermore, it is shown that by adding the intensity image sequence to the range information, one can prevent the equation system from falling in an ill-posed condition.>