Reference 3D Model Research Articles

THE REPRESENTATION OF CULTURAL HERITAGE FROM TRADITIONAL DRAWING TO 3D SURVEY: THE CASE STUDY OF CASAMARY’S ABBEY

In 3D survey the aspects most discussed in the scientific community are those related to the acquisition of data from integrated survey (laser scanner, photogrammetric, topographic and traditional direct), rather than those relating to the interpretation of the data. Yet in the methods of traditional representation, the data interpretation, such as that of the philological reconstruction, constitutes the most important aspect. It is therefore essential in modern systems of survey and representation, filter the information acquired. In the system, based on the integrated survey that we have adopted, the 3D object, characterized by a cloud of georeferenced points, defined but their color values, defines the core of the elaboration. It allows to carry out targeted analysis, using section planes as a tool of selection and filtering data, comparable with those of traditional drawings.<br><br> In the case study of the Abbey of Casamari (Veroli), one of the most important Cistercian Settlement in Italy, the survey made for an Agreement with the Ministry of Cultural Heritage and Activities and Tourism (MiBACT) and University of RomaTre, within the project "Accessment of the sismic safety of the state museum", the reference 3D model, consisting of the superposition and geo-references data from various surveys, is the tool with which yo develop representative models comparable to traditional ones. It provides the necessary spatial environment for drawing up plans and sections with a definition such as to develop thematic analysis related to phases of construction, state of deterioration and structural features.

THE REPRESENTATION OF CULTURAL HERITAGE FROM TRADITIONAL DRAWING TO 3D SURVEY: THE CASE STUDY OF CASAMARY’S ABBEY

Abstract. In 3D survey the aspects most discussed in the scientific community are those related to the acquisition of data from integrated survey (laser scanner, photogrammetric, topographic and traditional direct), rather than those relating to the interpretation of the data. Yet in the methods of traditional representation, the data interpretation, such as that of the philological reconstruction, constitutes the most important aspect. It is therefore essential in modern systems of survey and representation, filter the information acquired. In the system, based on the integrated survey that we have adopted, the 3D object, characterized by a cloud of georeferenced points, defined but their color values, defines the core of the elaboration. It allows to carry out targeted analysis, using section planes as a tool of selection and filtering data, comparable with those of traditional drawings. In the case study of the Abbey of Casamari (Veroli), one of the most important Cistercian Settlement in Italy, the survey made for an Agreement with the Ministry of Cultural Heritage and Activities and Tourism (MiBACT) and University of RomaTre, within the project "Accessment of the sismic safety of the state museum", the reference 3D model, consisting of the superposition and geo-references data from various surveys, is the tool with which yo develop representative models comparable to traditional ones. It provides the necessary spatial environment for drawing up plans and sections with a definition such as to develop thematic analysis related to phases of construction, state of deterioration and structural features.

3D-modeling of deformed halite hopper crystals by Object Based Image Analysis

Object Based Image Analysis (OBIA) is an established method for analyzing multiscale and multidimensional imagery in a range of disciplines. In the present study this method was used for the 3D reconstruction of halite hopper crystals in a mudrock sample, based on Computed Tomography data. To quantitatively assess the reliability of OBIA results, they were benchmarked against a corresponding “gold standard”, a reference 3D model of the halite crystals that was derived by manual expert digitization of the CT images. For accuracy assessment, classical per-scene statistics were extended to per-object statistics. The strength of OBIA was to recognize all objects similar to halite hopper crystals and in particular to eliminate cracks. Using a support vector machine (SVM) classifier on top of OBIA, unsuitable objects like halite crystal clusters, polyhalite-coated crystals and spherical halite crystals were effectively dismissed, but simultaneously the number of well-shaped halites was reduced.

A SURFACE-BASED ELECTROPHYSIOLOGY MODEL RELYING ON ASYMPTOTIC ANALYSIS AND MOTIVATED BY CARDIAC ATRIA MODELING

Computational electrophysiology is a very active field with tremendous potential in medical applications, albeit it leads to highly intensive simulations. We here propose a surface-based electrophysiology formulation, motivated by the modeling of thin structures such as cardiac atria, which greatly reduces the size of the computational models. Moreover, our model is specifically devised to retain the key features associated with the anisotropy in the diffusion effects induced by the fiber architecture, with rapid variations across the thickness that cannot be adequately represented by naive averaging strategies. Our proposed model relies on a detailed asymptotic analysis in which we identify a limit model and establish strong convergence results. We also provide detailed numerical assessments that confirm an excellent accuracy of the surface-based model – compared with the reference 3D model – including in the representation of a complex phenomenon, namely, spiral waves.

Space shuttle testing of the TriDAR 3D rendezvous and docking sensor

AbstractThis paper presents results from the first two Space Shuttle test flights of the TriDAR vision system. TriDAR was developed as a proximity operations sensor for autonomous rendezvous and docking (AR&D) missions to noncooperative targets in space. The system does not require the use of cooperative markers, such as retro‐reflectors, on the target spacecraft. TriDAR includes a hybrid three‐dimensional (3D) sensor along with embedded model based tracking algorithms to provide six‐degree‐of‐freedom (6 DOF) relative pose information in real time. A thermal imager is also included to provide range and bearing information for far‐range rendezvous operations. In partnership with the Canadian Space Agency (CSA) and NASA, Neptec has space‐qualified the TriDAR vision system and integrated it on board Space Shuttle Discovery to fly as a detailed test objective (DTO) on the STS‐128 and STS‐131 missions to the International Space Station (ISS). The objective of the TriDAR DTO missions was to demonstrate the system's ability to perform acquisition and tracking of a known target in space autonomously and provide real‐time relative navigation cues. Knowledge (reference 3D model) about the target can be obtained on the ground or in orbit. Autonomous operations involved automatic acquisition of the ISS and real‐time tracking, as well as detection and recovery from system malfunctions and/or loss of tracking. © 2012 Wiley Periodicals, Inc.

Acquisition of time-varying 3D foot shapes from video

The 3D scanning of time-varying objects based on multi-view geometry has been a hot topic in computer vision in recent years. This paper presents an active approach to acquiring 3D shapes of moving foot from multi-view video sequences based on the explicit marker points woven in socks. The reference 3D model of foot is firstly recovered from the starting frames in the multi-view video clips, and then the markers in each view are traced as a whole based on a continuous motion vector field built from the reference 3D model. The missing vertices in the candidate 3D model caused by self-occlusion, non-uniform illumination and random noises are reliably estimated and reconstructed in 3D space by minimizing the changes of differential features in 3D geometry of the reference model. The experimental results show that our method can robustly recover the 3D model of foot in complex background even if there is a relatively large movement between the adjacent frames, with an acceptable accuracy of the resulting 3D model.

2D approximation of realistic 3D vineyard row canopy representation for light interception ( fIPAR) and light intensity distribution on leaves ( LIDIL)

A detailed dynamic 3D architecture model coupled with a soil water balance model is used to explore the pertinence of 2D approximations of the row structure and describe the light regime and canopy photosynthesis in vineyard. The fraction of intercepted light ( fIPAR), the fraction of illuminated leaf area ( fILA) and the distribution of light intensity on illuminated leaves ( LIDIL) were calculated using Z-buffer and ray tracing techniques under both direct (black-sky) and diffuse (white-sky) conditions. The 2D approximations of the row were based on parallelepiped infinitely extended bounding boxes whose height and width was either defined by the outer envelope of the leaves (2D max) or effective dimensions (2D eff) adjusted to simulate the same instantaneous fIPAR diurnal time course as that of the reference 3D model (3D). The results showed consistent simulations between 2D eff and the reference 3D model for the three light regime variables investigated. Conversely, discrepancies were observed between 2D max and the reference 3D model both for fIPAR and fILA: the 2D max model overestimates the actual fIPAR (up to 22%) and fILA (up to 50% in some cases). These differences increased with LAI values, and are associated to an overestimation of row height. Conversely, LIDIL simulated for the 2D max were consistent with those obtained with both 3D and 2D eff models. The canopy level photosynthesis rates, computed using the leaf model of Schultz (2003), confirmed the adequacy of a 2D effective row structure approximation. The 2D max approximation leads to systematic overestimation of photosynthesis rates that can reach up to 36%. Although an effective 2D approximation seems very pertinent for light regime simulations in the PAR domain where multiple scattering is marginal, it was difficult to relate the effective dimensions to other canopy architecture features easy to measure in the field, row height being the most sensitive characteristic.

Segmentation process significantly influences the accuracy of 3D surface models derived from cone beam computed tomography

To assess the accuracy of surface models derived from 3D cone beam computed tomography (CBCT) with two different segmentation protocols. Seven fresh-frozen cadaver heads were used. There was no conflict of interests in this study. CBCT scans were made of the heads and 3D surface models were created of the mandible using two different segmentation protocols. The one series of 3D models was segmented by a commercial software company, while the other series was done by an experienced 3D clinician. The heads were then macerated following a standard process. A high resolution laser surface scanner was used to make a 3D model of the macerated mandibles, which acted as the reference 3D model or "gold standard". The 3D models generated from the two rendering protocols were compared with the "gold standard" using a point-based rigid registration algorithm to superimpose the three 3D models. The linear difference at 25 anatomic and cephalometric landmarks between the laser surface scan and the 3D models generate from the two rendering protocols was measured repeatedly in two sessions with one week interval. The agreement between the repeated measurement was excellent (ICC=0.923-1.000). The mean deviation from the gold standard by the 3D models generated from the CS group was 0.330mm±0.427, while the mean deviation from the Clinician's rendering was 0.763mm±0.392. The surface models segmented by both CS and DS protocols tend to be larger than those of the reference models. In the DS group, the biggest mean differences with the LSS models were found at the points ConLatR (CI: 0.83-1.23), ConMedR (CI: -3.16 to 2.25), CoLatL (CI: -0.68 to 2.23), Spine (CI: 1.19-2.28), ConAntL (CI: 0.84-1.69), ConSupR (CI: -1.12 to 1.47) and RetMolR (CI: 0.84-1.80). The Commercially segmented models resembled the reality more closely than the Doctor's segmented models. If 3D models are needed for surgical drilling guides or surgical planning which requires high precision, the additional cost of the commercial segmentation services seem to be justified to produce a more accurate surface models.

A multiresolution approach to orientation assignment in 3D electron microscopy of single particles

Three-dimensional (3D) electron microscopy (3DEM) aims at the determination of the spatial distribution of the Coulomb potential of macromolecular complexes. The 3D reconstruction of a macromolecule using single-particle techniques involves thousands of 2D projections. One of the key parameters required to perform such a 3D reconstruction is the orientation of each projection image as well as its in-plane orientation. This information is unknown experimentally and must be determined using image-processing techniques. We propose the use of wavelets to match the experimental projections with those obtained from a reference 3D model. The wavelet decomposition of the projection images provides a framework for a multiscale matching algorithm in which speed and robustness to noise are gained. Furthermore, this multiresolution approach is combined with a novel orientation selection strategy. Results obtained from computer simulations as well as experimental data encourage the use of this approach.

Fully Automatic Anatomical, Pathological, and Functional Segmentation from CT Scans for Hepatic Surgery

Objective: To improve the planning of hepatic surgery, we have developed a fully automatic anatomical, pathological, and functional segmentation of the liver derived from a spiral CT scan.Materials and Methods: From a 2 mm-thick enhanced spiral CT scan, the first stage automatically delineates skin, bones, lungs, kidneys, and spleen by combining the use of thresholding, mathematical morphology, and distance maps. Next, a reference 3D model is immersed in the image and automatically deformed to the liver contours. Then an automatic Gaussian fitting on the imaging histogram estimates the intensities of parenchyma, vessels, and lesions. This first result is next improved through an original topological and geometrical analysis, providing an automatic delineation of lesions and veins. Finally, a topological and geometrical analysis based on medical knowledge provides hepatic functional information that is invisible in medical imaging: portal vein labeling and hepatic anatomical segmentation according to the Couinaud classification.Results: Clinical validation performed on more than 30 patients shows that delineation of anatomical structures by this method is often more sensitive and more specific than manual delineation by a radiologist.Conclusion: This study describes the methodology used to create the automatic segmentation of the liver with delineation of important anatomical, pathological, and functional structures from a routine CT scan. Using the methods proposed in this study, we have confirmed the accuracy and utility of the creation of a 3D liver model compared with the conventional reading of the CT scan by a radiologist. This work may allow improved preoperative planning of hepatic surgery by more precisely delineating liver pathology and its relationship to normal hepatic structures. In the future, this data may be integrated with computer-assisted surgery and thus represents a first step towards the development of an augmented-reality surgical system.

Fully automatic anatomical, pathological, and functional segmentation from CT scans for hepatic surgery.

To improve the planning of hepatic surgery, we have developed a fully automatic anatomical, pathological, and functional segmentation of the liver derived from a spiral CT scan. From a 2 mm-thick enhanced spiral CT scan, the first stage automatically delineates skin, bones, lungs, kidneys, and spleen by combining the use of thresholding, mathematical morphology, and distance maps. Next, a reference 3D model is immersed in the image and automatically deformed to the liver contours. Then an automatic Gaussian fitting on the imaging histogram estimates the intensities of parenchyma, vessels, and lesions. This first result is next improved through an original topological and geometrical analysis, providing an automatic delineation of lesions and veins. Finally, a topological and geometrical analysis based on medical knowledge provides hepatic functional information that is invisible in medical imaging: portal vein labeling and hepatic anatomical segmentation according to the Couinaud classification. Clinical validation performed on more than 30 patients shows that delineation of anatomical structures by this method is often more sensitive and more specific than manual delineation by a radiologist. This study describes the methodology used to create the automatic segmentation of the liver with delineation of important anatomical, pathological, and functional structures from a routine CT scan. Using the methods proposed in this study, we have confirmed the accuracy and utility of the creation of a 3D liver model compared with the conventional reading of the CT scan by a radiologist. This work may allow improved preoperative planning of hepatic surgery by more precisely delineating liver pathology and its relationship to normal hepatic structures. In the future, this data may be integrated with computer-assisted surgery and thus represents a first step towards the development of an augmented-reality surgical system.

Indexing Based on Algebraic Functions of Views

In this paper, we propose the use of algebraic functions of views for indexing-based object recognition. During indexing, we consider groups of model points and we represent all the views (i.e., images) that they can produce in a hash table. The images that a group of model points can produce are computed by combining a small number of reference views which contain the group using algebraic functions of views. Fundamental to this procedure is a methodology, based on Singular Value Decomposition and Interval Arithmetic, for estimating the allowable ranges of values that the parameters of algebraic functions can assume. During recognition, scene groups are used to retrieve from the hash table the most feasible model groups that might have produced the scene groups. The use of algebraic functions of views for indexing-based recognition offers a number of advantages. First of all, the hash table can be built using a small number of reference views per object. This is in contrast to current approaches which build the hash table using either a large number of reference views or 3D models. Most importantly, recognition does not rely on the similarity between reference views and novel views; all that is required for the novel views is to contain common groups of points with a small number of reference views. Second, verification becomes simpler. This is because candidate models can now be back-projected onto the scene by applying a linear transformation on a small number of reference views of the candidate model. Finally, the proposed approach is more general and extendible. This is because algebraic functions of views have been shown to exist over a wide range of transformations and projections. The recognition performance of the proposed approach is demonstrated using both artificial and real data.