Herb Voelcker and his research team laid the foundations of Solid Modelling, on which Computer-Aided Design is based. He founded the ambitious Production Automation Project, that included Constructive Solid Geometry (CSG) as the basic 3D geometric representation. CSG trees were compact and robust, saving a memory space that was scarce in those times. But the main computational problem was Boundary Evaluation: the process of converting CSG trees to Boundary Representations (BReps) with explicit faces, edges and vertices for manufacturing and visualization purposes. This paper presents some glimpses of the history and evolution of some ideas that started with Herb Voelcker. We briefly describe the path from -localization and boundary evaluation- to -localization and printing-, with many intermediate steps driven by hardware, software and new mathematical tools: voxel and volume representations, triangle meshes, and many others, observing also that in some applications, voxel models no longer require Boundary Evaluation. In this last case, we consider the current research challenges and discuss several avenues for further research.

Slicing a model (computing thin slices of a geometric or volumetric model with a sweeping plane) is necessary for several applications ranging from 3D printing to medical imaging. This paper introduces a technique designed to compute these slices efficiently, even for huge and complex models. We voxelize the volume of the model at a required resolution and show how to encode this voxelization in an out-of-core octree using a novel Sweep Encoding linearization. This approach allows for efficient slicing with bounded cost per slice. We discuss specific applications, including 3D printing, and compare these octrees’ performance against the standard representations in the literature.

The study of the colonic volume is a procedure with strong relevance to gastroenterologists. Depending on the clinical protocols, the volume analysis has to be performed on MRI of the unprepared colon without contrast administration. In such circumstances, existing measurement procedures are cumbersome and time-consuming for the specialists. The algorithm presented in this paper permits a quasi-automatic segmentation of the unprepared colon on T2-weighted MRI scans. The segmentation algorithm is organized as a three-stage pipeline. In the first stage, a custom tubularity filter is run to detect colon candidate areas. The specialists provide a list of points along the colon trajectory, which are combined with tubularity information to calculate an estimation of the colon medial path. In the second stage, we delimit the region of interest by applying custom segmentation algorithms to detect colon neighboring regions and the fat capsule containing abdominal organs. Finally, within the reduced search space, segmentation is performed via 3D graph-cuts in a three-stage multigrid approach. Our algorithm was tested on MRI abdominal scans, including different acquisition resolutions, and its results were compared to the colon ground truth segmentations provided by the specialists. The experiments proved the accuracy, efficiency, and usability of the algorithm, while the variability of the scan resolutions contributed to demonstrate the computational scalability of the multigrid architecture. The system is fully applicable to the colon measurement clinical routine, being a substantial step towards a fully automated segmentation.

Normal vectors are essential for many point cloud operations, including segmentation, reconstruction and rendering. The robust estimation of normal vectors from 3D range scans is a challenging task due to undersampling and noise, specially when combining points sampled from multiple sensor locations. Our error model assumes a Gaussian distribution of the range error with spatially-varying variances that depend on sensor distance and reflected intensity, mimicking the features of Lidar equipment. In this paper we study the impact of measurement errors on the covariance matrices of point neighborhoods. We show that covariance matrices of the true surface points can be estimated from those of the acquired points plus sensordependent directional terms. We derive a lower bound on the neighbourhood size to guarantee that estimated matrix coefficients will be within a predefined error with a prescribed probability. This bound is key for achieving an optimal trade-off between smoothness and fine detail preservation. We also propose and compare different strategies for handling neighborhoods with samples coming from multiple materials and sensors. We show analytically that our method provides better normal estimates than competing approaches in noise conditions similar to those found in Lidar equipment.

Mobile devices have experienced an incredible market penetration in the last decade. Currently, medium to premium smartphones are relatively aordable devices. With the increase in screen size and resolution, together with the improvements in performance of mobile CPUs and GPUs, more tasks have become possible. In this paper we explore the rendering of medium to large volumetric models on mobile and low performance devices in general. To do so, we present a progressive ray casting method that is able to obtain interactive frame rates and high quality results for models that not long ago were only supported by desktop computers.

Obtaining 3D realistic models of urban scenes from accurate range data is nowadays an important research topic, with applications in a variety of fields ranging from Cultural Heritage and digital 3D archiving to monitoring of public works. Processing massive point clouds acquired from laser scanners involves a number of challenges, from data management to noise removal, model compression and interactive visualization and inspection. In this paper, we present a new methodology for the reconstruction of 3D scenes from massive point clouds coming from range lidar sensors. Our proposal includes a panorama-based compact reconstruction where colors and normals are estimated robustly through an error-aware algorithm that takes into account the variance of expected errors in depth measurements. Our representation supports efficient, GPU-based visualization with advanced lighting effects. We discuss the proposed algorithms in a practical application on urban and historical preservation, described by a massive point cloud of 3.5 billion points. We show that we can achieve compression rates higher than 97% with good visual quality during interactive inspections.

The use of virtual prototypes and digital models containing thousands of individual objects is commonplace in complex industrial applications like the cooperative design of huge ships. Designers are interested in selecting and editing specific sets of objects during the interactive inspection sessions. This is however not supported by standard visualization systems for huge models. In this paper we discuss in detail the concept of rendering front in multiresolution trees, their properties and the algorithms that construct the hierarchy and efficiently render it, applied to very complex CAD models, so that the model structure and the identities of objects are preserved. We also propose an algorithm for the interactive inspection of huge models which uses a rendering budget and supports selection of individual objects and sets of objects, displacement of the selected objects and real-time collision detection during these displacements. Our solution ---based on the analysis of several existing view-dependent visualization schemes--- uses a Hybrid Multiresolution Tree that mixes layers of exact geometry, simplified models and impostors, together with a time-critical, view-dependent algorithm and a Constrained Front. The algorithm has been successfully tested in real industrial environments; the models involved are presented and discussed in the paper.

Cage-based space deformations are often used to edit and animate images and geometric models. The deformations of the cage are easily transferred to the model by recomputing fixed convex combinations of the vertices of the cage, the control points. In current cage-based schemes the configuration of edges and facets between these control points affects the resulting deformations. In this paper we present a family of similar schemes that includes some of the current techniques, but also new schemes that depend only on the positions of the control points. We prove that these methods afford a solution under fairly general conditions and result in an easy and flexible way to deform objects using freely placed control points, with the necessary conditions of positivity and continuity.

Medical datasets are continuously increasing in size. Although larger models may be available for certain research purposes, in the common clinical practice the models are usually of up to 512×512×2000 voxels. These resolutions exceed the capabilities of conventional GPUs, the ones usually found in the medical doctors’ desktop PCs. Commercial solutions typically reduce the data by downsampling the dataset iteratively until it fits the available target specifications. The data loss reduces the visualization quality and this is not commonly compensated with other actions that might alleviate its effects. In this paper, we propose adaptive transfer functions, an algorithm that improves the transfer function in downsampled multiresolution models so that the quality of renderings is highly improved. The technique is simple and lightweight, and it is suitable, not only to visualize huge models that would not fit in a GPU, but also to render not-so-large models in mobile GPUs, which are less capable than their desktop counterparts. Moreover, it can also be used to accelerate rendering frame rates using lower levels of the multiresolution hierarchy while still maintaining high-quality results in a focus and context approach. We also show an evaluation of these results based on perceptual metrics.

We discuss bi-harmonic fields which approximate signed distance fields. We conclude that the biharmonic field approximation can be a powerful tool for mesh completion in general and complex cases. We present an adaptive, multigrid algorithm to extrapolate signed distance fields. By defining a volume mask in a closed region bounding the area that must be repaired, the algorithm computes a signed distance field in well-defined regions and uses it as an over-determined boundary condition constraint for the biharmonic field computation in the remaining regions. The algorithm operates locally, within an expanded bounding box of each hole, and therefore scales well with the number of holes in a single, complex model. We discuss this approximation in practical examples in the case of triangular meshes resulting from laser scan acquisitions which require massive hole repair. We conclude that the proposed algorithm is robust and general, and is able to deal with complex topological cases.

Recent advances in 3D scanning technologies have opened new possibilities in a broad range of applications including cultural heritage, medicine, civil engineering, and urban planning. Virtual Reality systems can provide new tools to professionals that want to understand acquired 3D models. In this review paper, we analyze the concept of data comprehension with an emphasis on visualization and inspection tools on immersive setups. We claim that in most application fields, data comprehension requires model measurements, which in turn should be based on the explicit visualization of uncertainty. As 3D digital representations are not faithful, information on their fidelity at local level should be included in the model itself as uncertainty bounds. We propose the concept of Measurable 3D Models as digital models that explicitly encode such local uncertainty bounds. We claim that professionals and experts can strongly benefit from immersive interaction through new specific, fidelity-aware measurement tools, which can facilitate 3D data comprehension. Since noise and processing errors are ubiquitous in acquired datasets, we discuss the estimation, representation, and visualization of data uncertainty. We show that, based on typical user requirements in Cultural Heritage and other domains, application-oriented measuring tools in 3D models must consider uncertainty and local error bounds. We also discuss the requirements of immersive interaction tools for the comprehension of huge 3D and nD datasets acquired from real objects.

In this paper, we present an inexpensive approach to create highly detailed reconstructions of the landscape surrounding a road. Our method is based on a space-efficient semi-procedural representation of the terrain and vegetation supporting high-quality real-time rendering not only for aerial views but also at road level. We can integrate photographs along selected road stretches. We merge the point clouds extracted from these photographs with a low-resolution digital terrain model through a novel algorithm which is robust against noise and missing data. We pre-compute plausible locations for trees through an algorithm which takes into account perceptual cues. At runtime we render the reconstructed terrain along with plants generated procedurally according to pre-computed parameters. Our rendering algorithm ensures visual consistency with aerial imagery and thus it can be integrated seamlessly with current virtual globes.

Interactive visualization of volume models in standard mobile devices is a challenging present problem with increasing interest from new application fields like telemedicine. The complexity of present volume models in medical applications is continuously increasing, therefore increasing the gap between the available models and the rendering capabilities in low-end mobile clients. New and efficient rendering algorithms and interaction paradigms are required for these small platforms. In this paper, we propose a transfer function-aware compression and interaction scheme, for client-server architectures with visualization on standard mobile devices. The scheme is block-based, supporting adaptive ray-casting in the client. Our two-level ray-casting allows focusing on small details on targeted regions while keeping bounded memory requirements in the GPU of the client. Our approach includes a transfer function-aware compression scheme based on a local wavelet transformation, together with a bricking scheme that supports interactive inspection and levels of detail in the mobile device client. We also use a quantization technique that takes into account a perceptive metrics of the visual error. Our results show that we can have full interaction with high compression rates and with transmitted model sizes that can be of the order of a single photographic image.

Computer Graphics and Virtual Reality technologies provide powerful tools for visualizing, documenting and disseminating cultural heritage. Virtual inspection tools have been used proficiently to show cultural artifacts either through the web or in museum exhibits. The usability of the user interface has been recognized to play a crucial role in overcoming the typical fearful attitude of the cultural heritage community towards 3D graphics. In this paper we discuss the design of the user interface for the virtual inspection of the impressive entrance of the Ripoll Monastery in Spain. The system was exhibited in the National Art Museum of Catalonia (MNAC) during 2008 and since June 2011 it is part of its Romanesque exhibition. The MNAC is the third most visited art museum in Spain, and features the world?s largest collection on Romanesque Art. We analyze the requirements from museum curators and discuss the main interface design decisions. The user interface combines (a) focus-plus-context visualization, with focus (detail view) and context (overview) being shown at separate displays, (b) touch-based camera control techniques, and (c) continuous feedback about the exact location of the detail area within the entrance. The interface allows users to aim the camera at any point of the entrance with centimeter accuracy using a single tap. We provide the results of a user study comparing our user interface with alternative approaches. We also discuss the benefits the exhibition had to the cultural heritage community.

In this paper, we propose a novel strategy to automatically segment volume data using a high-quality mesh segmentation of an "example" model as a guiding example. The example mesh is deformed until it matches the relevant volume features. The algorithm starts from a medical volume model (scalar field of densities) to be segmented, together with an already existing segmentation (polygonal mesh) of the same organ, usually from a different person. The pre-process step computes a suitable atracting scalar field in the volume model. After an approximate 3D registration between the example mesh and the volume (this is the only step requiring user intervention), the algorithm works by minimizing an energy and adapts the shape of the polygonal mesh to the volume features in order to segment the target organ. The resulting mesh adapts to the volume features in the areas which can be unambiguously segmented, while taking the shape of the example mesh in regions which lack relevant volume information. The paper discusses several examples involving human foot bones, with results that clearly outperform present segmentation schemes.

The dichotomy between full detail representation and the efficient management of data digitization is still a big issue in the context of the acquisition and visualization of 3D objects, especially in the field of the Cultural Heritage. Modern scanning devices enable very detailed geometry to be acquired, but it is usually quite hard to apply these technologies to large artifacts. In this paper we present a project aimed at virtually reconstructing the impressive (7x11 m.) portal of the Ripoll Monastery, Spain. The monument was acquired using triangulation laser scanning technology, producing a dataset of 2212 range maps for a total of more than 1 billion triangles. All the steps of the entire project are described, from the acquisition planning to the final setup for dissemination to the public. We show how time-of-flight laser scanning data can be used to speed-up the alignment process. In addition we show how, after creating a model and repairing imperfections, an interactive and immersive setup enables the public to navigate and display a fully detailed representation of the portal. This paper shows that, after careful planning and with the aid of state-of-the-art algorithms, it is now possible to preserve and visualize highly detailed information, even for very large surfaces.

In this paper, we present an efficient approach for the interactive rendering of large-scale urban models, which can be integrated seamlessly with virtual globe applications. Our scheme fills the gap between standard approaches for distant views of digital terrains and the polygonal models required for close-up views. Our work is oriented towards city models with real photographic textures of the building facades. At the heart of our approach is a multi-resolution tree of the scene defining multi-level relief impostors. Key ingredients of our approach include the pre-computation of a small set of zenithal and oblique relief maps that capture the geometry and appearance of the buildings inside each node, a rendering algorithm combining relief mapping with projective texture mapping which uses only a small subset of the pre-computed relief maps, and the use of wavelet compression to simulate two additional levels of the tree. Our scheme runs considerably faster than polygonal-based approaches while producing images with higher quality than competing relief-mapping techniques. We show both analytically and empirically that multi-level relief impostors are suitable for interactive navigation through large urban models.

Limitations of current 3D acquisition technology often lead to polygonal meshes exhibiting a number of geometrical and topological defects which prevent them from widespread use. In this paper we present a new method for model repair which takes as input an arbitrary polygonal mesh and outputs a valid 2-manifold triangle mesh. Unlike previous work, our method allows users to quickly identify areas with potential topological errors and to choose how to fix them in a user-friendly manner. Key steps of our algorithm include the conversion of the input model into a set of voxels, the use of morphological operators to allow the user to modify the topology of the discrete model, and the conversion of the corrected voxel set back into a 2-manifold triangle mesh. Our experiments demonstrate that the proposed algorithm is suitable for repairing meshes of a large class of shapes.

In constructing a model of a large twelfth century monument, we face the repair of a huge amount of small to medium-sized defects in the mesh. The total size of the mesh after registration was in the vicinity of 173M-triangles, and presented 14,622 holes of different sizes. Although other algorithms have been presented in the literature to fix these defects, in this case a fully automatic algorithm able to fix most of the defects is needed. In this paper we present the algorithms developed for this purpose, together with examples and results to measure the final surface quality. The algorithm is based on the iteration of smoothing and fitting steps on a uniform B-Spline defined on a 3D box domain bounding the hole. Tricubic and trilinear B-Splines are compared and the respective effectiveness is discussed.

We present "Pressing", an algorithm for smoothing isosurfaces extracted from binary volumes while recovering their large planar regions (flats). Pressing yields a surface that is guaranteed to contain the samples of the volume classified as interior and exclude those classified as exterior. It uses global optimization to identify flats and constrained bilaplacian smoothing to eliminate sharp features and high-frequencies from the rest of the isosurface. It recovers sharp edges between flat regions and between flat and smooth regions. Hence, the resulting isosurface is usually a much more accurate approximation of the original solid than isosurfaces produced by previously proposed approaches. Furthermore, the segmentation of the isosurface into flat and curved faces and the sharp/smooth labelling of their edges may be valuable for shape recognition, simplification, compression, and various reverse engineering and manufacturing applications.

Since the publication of the original Marching Cubes algorithm, numerous variations have been proposed for guaranteeing water-tight constructions of triangulated approximations of isosurfaces. Most approaches divide the 3D space into cubes that each occupy the space between eight neighboring samples of a regular lattice. The portion of the isosurface inside a cube may be computed independently of what happens in the other cubes, provided that the constructions for each pair of neighboring cubes agree along their common face. The portion of the isosurface associated with a cube may consist of one or more connected components, which we call sheets. The topology and combinatorial complexity of the isosurface is influenced by three types of decisions made during its construction: (1) how to connect the four intersection points on each ambiguous face, (2) how to form interpolating sheets for cubes with more than one loop, and (3) how to triangulate each sheet. To determine topological properties, it is only relevant whether the samples are inside or outside the object, and not their precise value, if there is one. Previously reported techniques make these decisions based on local —per cube — criteria, often using precomputed look-up tables or simple construction rules. Instead, we propose global strategies for optimizing several topological and combinatorial measures of the isosurfaces: triangle count, genus, and number of shells. We describe efficient implementations of these optimizations and the auxiliary data structures developed to support them.

The computation of the largest planar region approximating a 3D object is an important problem with wide applications in modeling and rendering. Given a voxelization of the 3D object, we propose an efficient algorithm to solve a discrete version of this problem. The input of the algorithm is the set of grid edges connecting the interior and the exterior of the object (called sticks). Using a voting-based approach, we compute the plane that slices the largest number of sticks and is orientation-compatible with these sticks. The robustness and efficiency of our approach rests on the use of two different parameterizations of the planes with suitable properties. The first of these is exact and is used to retrieve precomputed local solutions of the problem. The second one is discrete and is used in a hierarchical voting scheme to compute the global maximum. This problem has diverse applications that range from finding object signatures to generating simplified models. Here we demonstrate the merits of the algorithm for efficiently computing an optimized set of textured impostors for a given polygonal model.

Structure-from-motion along with multi-view stereo techniques jointly allow for the inexpensive scanning of 3D objects (e.g. buildings) using just a collection of images taken from commodity cameras. Despite major advances in these fields, a major limitation of dense reconstruction algorithms is that correct depth/normal values are not recovered on specular surfaces (e.g. windows) and parts lacking image features (e.g. flat, textureless parts of the facade). Since these reflective properties are inherent to the surface being acquired, images from different viewpoints hardly contribute to solve this problem. In this paper we present a simple method for detecting, classifying and filling non-valid data regions in depth maps produced by dense stereo algorithms. Triangles meshes reconstructed from our repaired depth maps exhibit much higher quality than those produced by state-of-the-art reconstruction algorithms like Screened Poisson-based techniques.

Virtual Reality (VR) simulations have long been proposed to allow users to explore both yet-to-built buildings in architectural design, and ancient, remote or disappeared buildings in cultural heritage. In this paper we describe an on-going VR project on an UNESCO World Heritage Site that simultaneously addresses both scenarios: supporting architects in the task of designing the remaining parts of a large unfinished building, and simulating existing parts that define the environment that new designs must conform to. The main challenge for the team of architects is to advance towards the project completion being faithful to the original Gaudí’s project, since many plans, drawings and plaster models were lost. We analyze the main requirements for collaborative architectural design in such a unique scenario, describe the main technical challenges, and discuss the lessons learned after one year of use of the system.

About 50% of the patients consulting a gastroenterology clinic report symptoms without detectable cause. Clinical researchers are interested in analyzing the volumetric evolution of colon segments under the effect of different diets and diseases. These studies require noninvasive abdominal MRI scans without using any contrast agent. In this work, we propose a colon segmentation framework designed to support T2-weighted abdominal MRI scans obtained from an unprepared colon. The segmentation process is based on an efficient and accurate quasiautomatic approach that drastically reduces the specialist interaction and effort with respect other state-of-the-art solutions, while decreasing the overall segmentation cost. The algorithm relies on a novel probabilistic tubularity filter, the detection of the colon medial line, probabilistic information extracted from a training set and a final unsupervised clustering. Experimental results presented show the benefits of our approach for clinical use.

The way in which gradients are computed in volume data-sets influences both the quality of the shading and the performance obtained in rendering algorithms. In particular, the visualization of coarse datasets in multi-resolution representations is affected when gradients are evaluated on-the-fly in the shader code by accessing neighbouring positions. We propose a downsampling filter for pre-computed gradients that provides improved gradients that better match the originals such that the aforementioned artifacts disappear. Secondly, to address the storage problem, we present a method for the efficient storage of gradient directions that is able to minimize the minimum angle achieved among all representable vectors in a space of 3 bytes.

Volume visualization software usually has to deal with datasets that are larger than the GPUs may hold. This is especially true in one of the most popular application scenarios: medical visualization. In this paper we explore the quality of different downsampling methods and present a new approach that produces smooth lower-resolution representations, yet still preserves small features that are prone to disappear with other approaches.

In the medical imaging field, interactive direct volume rendering of large volume datasets is a challenging task.Multi-resolution techniques deal with this problem by downsampling the original dataset to produce coarser rep-resentations. We present an evaluation of different downsampling filters with respect to their effectiveness at pre-serving details of the original dataset. Moreover, we propose a new Gaussian-based filter that produces qualitylower-resolution representations and preserves small features that are prone to disappear.

Nowadays, an increasing interest on tele-medicine and tele-diagnostic solutions can be observed, with client/server architectures for remote inspection of volume image-based medical data which are becoming more and more popular. The use of portable devices is gradually spreading due to their portability and easy maintenance. In this paper, we present an efficient data model for segmented volume models based on a hierarchical data structure of surfels per anatomical structure. Surfel Octrees are compact enough for transmission through networks with limited bandwidth, and provide good visual quality in the client devices at a limited footprint. Anatomy atlases are represented as octree forests, supporting local interaction in the client device and selection of groups of medical organs. After presenting the octree generation and interaction algorithms, we present several examples and discuss the interest of the proposed approach in low-end devices such as mobiles and tablets

In this paper, a novel four wall, passive stereo multi-projector CAVE architecture is presented. It is powered by 40 ¿possibly different¿ off the shelf DLP projectors controlled by 12 PCs. We have achieved high resolution while significantly reducing the overall cost, resulting on a high brigthness, 2000 x 2000 pixel resolution on each of the 4 walls. The AdaptiveCave VR System has an increased versatility both in terms of projectors and screen architecture. First, the system works with any mix of a wide range of projector models that can be substituted ¿one by one¿ at any moment, for more modern or cheaper ones. Second, the self-calibration software, which guarantees a uniform final image with concordance and continuity, can be adapted to many other wall and screen configurations. The AdaptiveCave project includes the set-up and all related software components: geometric and chromatic calibration, simultaneous rendering on 40 projected viewports, synchronization and interaction. The interaction is based on a cableless, kinect-based gesture interface with natural interaction paradigms.

Handling three-dimensional information during the remote visualization of medical images in tele-medicine requires efficient systems to achieve fast data transmission and interactive visualization. Client-server architectures meet these functionalities. The use of mobile devices is sometimes required due to the portability and easy maintenance, but issues like transmission time for the volumetric information and low performance hardware properties must be addressed. We present a hybrid visualization approach which is based on two transfer-function aware models. Given a user defined region of interest (ROI), the client stores a low resolution wavelet-based model of the volume data, and a ROI-dependent high resolution model based on gradient-octrees. This last model is only sent to the client when the ROI is changed. Interaction in the client is autonomous (without any data transmission) while the ROI is inspected. The results show that our hybrid approach is compact, efficient and scalable, with compression rates that decrease when the size of the volume model increases.

Remote exploration of medical volume models is nowadays a challenging problem. Interactive visualization algorithms must be able to send and render in real-time the volume model at the maximum possible visual quality, while adapting to network bandwidth limitations and to hardware constraints in the client device. In this paper we present a transfer function-aware scheme for the remote interactive inspection of volume models in client-server architectures with the objectives of supporting multi-resolution, avoiding gradient computations in the client device and sending a very limited amount of information through the network. Gradient Octrees can be progressively transmitted to the clients in a strongly compact way while achieving a minimum loss of visual quality as compared to state of the art ray-casting renderings. Visual volume understanding can be complemented by showing 2D sections of the original volume data on demand.

We propose a new deformation scheme for polygonal meshes through generalized barycentric coordinates that does not require any explicit cage definition. Our system infers the connectivity of the control points defined by the user and computes the coordinates using this structure. This allows the user to incrementally position the control points (or delete them) wherever he considers more suitable. This freedom gives more control, precision and locality to the deformation process.

The learning process in neurosurgery is a large and difficult task based on experimentation, being ventriculostomy not an exception. We have developed a virtual reality system to help training novel surgeons on this kind of operation. The system consists of the simulation of the surgery using a haptic device and a subsequent 3D visual inspection of the surgical trajectory. Our main objective was to proof that the tactile sensation produced by our system was enough realistic for the surgeons. We carried out a demonstration session in a medical workshop where all surgeons attending the workshop used the system with a very enthusiastic response about the perception experimented through the system.

The cage-based deformation of a 3D object through generalized barycentric coordinates is a simple, e fficient, effective and hence widely used shape manipulation scheme. Editing vertices of the polyhedral cage induces a smooth space deformation of its interior; the vertices thus become control handles of the final deformation. However, in some application fi elds, as medicine, constrained volume preserving deformations are required. In this paper, we present a solution that takes advantage of the potential of the deformations based on generalized barycentric coordinates while adding the constraint of keeping a volume constant. An implementation of the proposed scheme is presented and discussed. A measure of local stress of the deformed volume is also proposed.

The dichotomy between detail representation and data management is still a big issue in the context of the acquisition and visualization of 3D objects, especially in the field of Cultural Heritage. New technologies give the possibility to acquire very detailed geometry, but very often it’s very hard to process the amount of data produced. In this paper we present a project which aimed at virtually reconstructing the impressive (7x11 m.) portal of the Ripoll Monastery, Spain. The monument was acquired using triangulation laser scanning technology, producing a dataset of more than 2000 range maps for a total of more than 1 billion triangles. All the steps of the entire project are described, from the acquisition planning to the final setup for the dissemination to the public. In particular, we show how timeof- flight laser scanning data can be used to obtain a speed up in the alignment process, and how, after model creation and imperfections repairing, an interactive and immersive setup gives the public the possibility to navigate and visualize the high detail representation of the portal. This paper shows that, after careful planning and with the aim of new algorithms, it’s now possible to preserve and visualize the highly detailed information provided by triangulation laser scanning also for very large surfaces.

This paper presents the project of the virtual reconstruction and inspection of the "Portalada", the entrance of the Ripoll Monastery. In a first step, the monument of 7 x 11 meters was acquired using triangulation laser scanning technology, producing a dataset of more than 2000 range maps for a total of more than one billion triangles. After alignment and registration, a nearly complete digital model with 173M triangles and a sampling density of the order of one millimeter was produced and repaired. The paper describes the model acquisition and construction, the use of specific scalable algorithms for model repair and simplification, and then focuses on the design of a hierarchical data structure for data managing and view-dependent navigation of this huge dataset on a PC. Finally, the paper describes the setup for a usable, user-friendly and immersive system that induces a presence perception in the visitors.