Large 3D Models Research Articles

S-LPM: segmentation augmented light-weighting and progressive meshing for the interactive visualization of large man-made Web3D models

With the advent of the era of “big data”, increasing efforts have been focused on how to process large models to improve transmission over the internet and display in a browser, i.e., Web3D technology. Notwithstanding the many new advancements in Web3D technology, because browsers have limited storage capacity and low computational ability, the efficient display of a large model through the net remains a bottleneck problem. This paper proposes a light-weighting visualization framework, called the S-LPM framework, which includes a novel Dijkstra-based mesh segmentation operation and a new voxel-based repetition detection/removal operation to efficiently display large 3D models in a Web browser. The two key geometric operations substantially reduce the amount of data transmitted over the net, which in turn significantly increases the transmission speed. The partially transmitted data are then aligned through transformations to restore the entire original model and display it in the Web browser. The experimental results show that our approach is generally accurate and feasible, and its performance is superior to that of the benchmarking methods.

FeatureNet: Machining feature recognition based on 3D Convolution Neural Network

Automated machining feature recognition, a sub-discipline of solid modeling, has been an active research area for last three decades and is a critical component in digital manufacturing thread for detecting manufacturing information from computer aided design (CAD) models. In this paper, a novel framework using Deep 3D Convolutional Neural Networks (3D-CNNs) termed FeatureNet to learn machining features from CAD models of mechanical parts is presented. FeatureNet learns the distribution of complex manufacturing feature shapes across a large 3D model dataset and discovers distinguishing features that help in recognition process automatically. To train FeatureNet, a large-scale mechanical part datasets of 3D CAD models with labeled machining features is automatically constructed. The proposed framework can recognize manufacturing features from the low-level geometric data such as voxels with a very high accuracy. The developed framework can also recognize planar intersecting features in the 3D CAD models. Extensive numerical experiments show that FeatureNet enables significant improvements over the state-of-the-arts manufacturing feature detection techniques. The developed data-driven framework can easily be extended to identify a large variety of machining features leading to a sound foundation for real-time computer aided process planning (CAPP) systems.

Unsupervised texture transfer from images to model collections

Large 3D model repositories of common objects are now ubiquitous and are increasingly being used in computer graphics and computer vision for both analysis and synthesis tasks. However, images of objects in the real world have a richness of appearance that these repositories do not capture, largely because most existing 3D models are untextured. In this work we develop an automated pipeline capable of transporting texture information from images of real objects to 3D models of similar objects. This is a challenging problem, as an object's texture as seen in a photograph is distorted by many factors, including pose, geometry, and illumination. These geometric and photometric distortions must be undone in order to transfer the pure underlying texture to a new object --- the 3D model. Instead of using problematic dense correspondences, we factorize the problem into the reconstruction of a set of base textures (materials) and an illumination model for the object in the image. By exploiting the geometry of the similar 3D model, we reconstruct certain reliable texture regions and correct for the illumination, from which a full texture map can be recovered and applied to the model. Our method allows for large-scale unsupervised production of richly textured 3D models directly from image data, providing high quality virtual objects for 3D scene design or photo editing applications, as well as a wealth of data for training machine learning algorithms for various inference tasks in graphics and vision.

City-Scale Localization for Cameras with Known Vertical Direction

We consider the problem of localizing a novel image in a large 3D model, given that the gravitational vector is known. In principle, this is just an instance of camera pose estimation, but the scale of the problem introduces some interesting challenges. Most importantly, it makes the correspondence problem very difficult so there will often be a significant number of outliers to handle. To tackle this problem, we use recent theoretical as well as technical advances. Many modern cameras and phones have gravitational sensors that allow us to reduce the search space. Further, there are new techniques to efficiently and reliably deal with extreme rates of outliers. We extend these methods to camera pose estimation by using accurate approximations and fast polynomial solvers. Experimental results are given demonstrating that it is possible to reliably estimate the camera pose despite cases with more than 99 percent outlier correspondences in city-scale models with several millions of 3D points.

3D model classification via Principal Thickness Images

With the innovation in 3D modeling software, more and more 3D models are becoming available in recent decades. To facilitate efficient retrieval and search of large 3D model databases, an effective shape classification algorithm is badly in need. In this paper, we propose a new feature descriptor named Principal Thickness Images (PTI) that encodes the boundary surface and the voxelized constituents of a 3D shape into three gray-scale images. With the support of PTI, we extend the kernel sparse representation-based classification from 2D case to non-rigid 3D models. Our classification algorithm inherits the robustness of kernel sparse representation and is able to achieve a high success rate and strong reliability on non-rigid models from the SHREC’11 non-rigid 3D models dataset. Numerous tests demonstrate superior performance of the proposed method over previous 3D shape classification approaches.

Thermal load-induced notch stress intensity factors derived from averaged strain energy density

Under the hypothesis of steady-state heat transfer and plane-strain conditions, the intensity of the stress distributions ahead of sharp V-notch tips can be expressed in terms of thermal notch stress intensity factors (thermal NSIFs) which can be used for fatigue strength assessments of notched components. The calculation of thermal NSIFs requires both an uncoupled thermal-mechanical numerical analysis and a very refined mesh. For these reasons, the numerical simulation becomes considerably expensive and time-consuming above all if large 2D or 3D models have to be solved. Refined meshes are not necessary when the aim of the finite element analysis is to determine the mean value of the local strain energy density on a control volume surrounding the points of stress singularity. On the other hand, the NSIFs value can be directly determined by the strain energy density. In this work, the method for rapid calculations of NSIFs based on averaged strain energy density, recently published in literature, is extended to thermal problems.

Active Exploration of Large 3D Model Repositories.

With broader availability of large-scale 3D model repositories, the need for efficient and effective exploration becomes more and more urgent. Existing model retrieval techniques do not scale well with the size of the database since often a large number of very similar objects are returned for a query, and the possibilities to refine the search are quite limited. We propose an interactive approach where the user feeds an active learning procedure by labeling either entire models or parts of them as "like" or "dislike" such that the system can automatically update an active set of recommended models. To provide an intuitive user interface, candidate models are presented based on their estimated relevance for the current query. From the methodological point of view, our main contribution is to exploit not only the similarity between a query and the database models but also the similarities among the database models themselves. We achieve this by an offline pre-processing stage, where global and local shape descriptors are computed for each model and a sparse distance metric is derived that can be evaluated efficiently even for very large databases. We demonstrate the effectiveness of our method by interactively exploring a repository containing over 100K models.

The Garden Banks model experience

To better understand deepwater imaging challenges in the Gulf of Mexico, we constructed a large 3D model based on the complex salt geology of the Garden Banks protraction area. We simulated a regional wide-azimuth (WAZ) streamer survey with offsets of ±8 km inline and ±4 km crossline over this model. Using the true velocity model, reverse time migration of this data set produced a usable subsalt image nearly everywhere. The same synthetic seismic data set was passed to interpreters and geophysicists to process and image as if it were real field data. They did not get to see the true velocity model. Instead they performed conventional “migrate, pick, and flood” top-down velocity-model building, followed by final imaging through their interpreted velocity model. Where the salt was relatively simple, we found that the interpreted velocity model was reasonably accurate. Reverse time migration of the seismic data through these parts of the velocity model produced an image that was imperfect, but still usable for exploration-scale, structural interpretation. Where the salt structure was complex, however, it was sometimes grossly misinterpreted. The ensuing large-scale errors in the interpreted velocity model resulted in an unusable, shattered subsalt image. We next simulated a low-frequency, ocean-bottom-node (OBN) acquisition, with offsets up to 30 km in all azimuths. We started with the imperfect model produced by the interpreters and investigated what it would take for full-waveform inversion (FWI) to successfully find and fix the gross interpretation errors. Initial results suggest this “interpretation followed by FWI” methodology could produce a velocity model capable of generating an adequate subsalt image, but it may require ultrawide offsets (30 km), ultralow frequencies (below 2 Hz), and improved FWI algorithms to do so.

Improving the communication performance of distributed animation rendering using BitTorrent file system

Rendering is a crucial process in the production of computer generated animation movies. It executes a computer program to transform 3D models into series of still images, which will eventually be sequenced into a movie. Due to the size and complexity of 3D models, rendering process becomes a tedious, time-consuming and unproductive task on a single machine. Accordingly, animation rendering is commonly carried out in a distributed computing environment where numerous computers execute in parallel to speedup the rendering process. In accordance with distribution of computing, data dissemination to all computers also needs certain mechanisms which allow large 3D models to be efficiently moved to those distributed computers to ensure the reduction of time and cost in animation production. This paper presents and evaluates BitTorrent file system (BTFS) for improving the communication performance of distributed animation rendering. The BTFS provides an efficient, secure and transparent distributed file system which decouples the applications from complicated communication mechanism. By having data disseminated in a peer-to-peer manner and using local cache, rendering time can be reduced. Its performance comparison with a production-grade 3D animation favorably shows that the BTFS outperforms traditional distributed file systems by more than 3 times in our test configuration.

Rotational alignment of the distal femur: anthropometric measurements with CT-based patient-specific instruments planning show high variability of the posterior condylar angle.

Finding the anatomical landmarks used for correct femoral axial alignment can be difficult. The posterior condylar line (PCL) is probably the easiest to find during surgery. The aim of this study was to analyse whether a predetermined fixed angle referencing of the PCL could help find the surgical epicondylar axis (SEA) and this based on a large CT database with enough Caucasian diversity to be representable. A total of 2,637 CT scans and 3D reconstructions from patients on four continents, executed for preoperative planning and creation of patient-specific instrumentation, were used to perform anthropometric measurements and to measure the posterior condylar angle (PCA) between the surgical epicondylar angle and the PCL. The mean (SD) PCA was 4° (1.4°) of external rotation. A significant correlation was found between more external rotation of the SEA and more proximal varus of the tibia or more distal valgus of the femur. For 59% of the study population, 4° external rotation from the PCL would be the right amount of axial rotation to align the femoral component in line with the SEA. Nine per cent needs less, and 32% needs more than 4° of axial rotation. On 105 (4%) CT-based 3D models, external rotation between 7° and 11° was measured and 77 (73%) of those cases were in varus or neutral alignment. In 132 patients, bilateral measurements were available and 94 (71%) had rotation within 1° of the opposite side. This last finding underlines that there is even an intra-individual difference in distal femoral anatomy that can range from 1° to 5°. This study was performed on a very large anthropometric CT and 3D models database and showed that there is a 41% risk of malalignment if a fixed PCA referenced of the PCL is used in total knee arthroplasty. The clinical importance of this study is the observation that femoral axial anatomy is individual and also that it is determined by the tibial anatomy. A group of patients needs more than the average external rotation because they have more distal femoral valgus with dysplastic condyles or more proximal tibial varus with a bigger medial condyle. III.

Painting-to-3D model alignment via discriminative visual elements

This article describes a technique that can reliably align arbitrary 2D depictions of an architectural site, including drawings, paintings, and historical photographs, with a 3D model of the site. This is a tremendously difficult task, as the appearance and scene structure in the 2D depictions can be very different from the appearance and geometry of the 3D model, for example, due to the specific rendering style, drawing error, age, lighting, or change of seasons. In addition, we face a hard search problem: the number of possible alignments of the painting to a large 3D model, such as a partial reconstruction of a city, is huge. To address these issues, we develop a new compact representation of complex 3D scenes. The 3D model of the scene is represented by a small set of discriminative visual elements that are automatically learned from rendered views. Similar to object detection, the set of visual elements, as well as the weights of individual features for each element, are learned in a discriminative fashion. We show that the learned visual elements are reliably matched in 2D depictions of the scene despite large variations in rendering style (e.g., watercolor, sketch, historical photograph) and structural changes (e.g., missing scene parts, large occluders) of the scene. We demonstrate an application of the proposed approach to automatic rephotography to find an approximate viewpoint of historical paintings and photographs with respect to a 3D model of the site. The proposed alignment procedure is validated via a human user study on a new database of paintings and sketches spanning several sites. The results demonstrate that our algorithm produces significantly better alignments than several baseline methods.

Three-dimensional (3D) CAD model lightweight scheme for large-scale assembly and simulation

Three-dimensional (3D) models are the most important carriers of CAD/CAE/CAPP/CAM, and usually they contain more information than practically needed as for some given applications, which may occupy superfluous storage space in computers. As a result, the handling speed also inevitably becomes slow, and certain inner secrets may be disclosed in the collaborative environment. The lightweight of large 3D models is an effectual solution. In this paper, a lightweight algorithm with intelligent information reduction for large-scale assembly is proposed to generate simple model by using their intrinsic structures. This algorithm aims at reducing the sizes of 3D CAD models within five steps and three levels from coarse to fine: components (including sub-assemblies and parts), feature and exterior geometry. Key strategies, such as components suppression, feature simplification and hollows seaming, are used in the processing. Finally, a shell model is created to represent the original one in subsequent applications. Different from 3D meshed model simplification, the proposed method is capable of reserving all necessary assembly interfaces for the further usage. Later experiments show that the lightweight method can obtain satisfactory results in practical design with preferable performance. The lightweight technology can be widely applied in many fields such as large-scale virtual assembly and movement simulation.

Surface and Curve Skeletonization of Large 3D Models on the GPU

We present a GPU-based framework for extracting surface and curve skeletons of 3D shapes represented as large polygonal meshes. We use an efficient parallel search strategy to compute point-cloud skeletons and their distance and feature transforms (FTs) with user-defined precision. We regularize skeletons by a new GPU-based geodesic tracing technique which is orders of magnitude faster and more accurate than comparable techniques. We reconstruct the input surface from skeleton clouds using a fast and accurate image-based method. We also show how to reconstruct the skeletal manifold structure as a polygon mesh and the curve skeleton as a polyline. Compared to recent skeletonization methods, our approach offers two orders of magnitude speed-up, high-precision, and low-memory footprints. We demonstrate our framework on several complex 3D models.

Inverse design of urban procedural models

We propose a framework that enables adding intuitive high level control to an existing urban procedural model. In particular, we provide a mechanism to interactively edit urban models, a task which is important to stakeholders in gaming, urban planning, mapping, and navigation services. Procedural modeling allows a quick creation of large complex 3D models, but controlling the output is a well-known open problem. Thus, while forward procedural modeling has thrived, in this paper we add to the arsenal an inverse modeling tool. Users, unaware of the rules of the underlying urban procedural model, can alternatively specify arbitrary target indicators to control the modeling process. The system itself will discover how to alter the parameters of the urban procedural model so as to produce the desired 3D output. We label this process inverse design.

A GPU‐based Approach for Massive Model Rendering with Frame‐to‐Frame Coherence

AbstractRendering massive 3D models in real‐time has long been recognized as a very challenging problem because of the limited computational power and memory space available in a workstation. Most existing rendering techniques, especially level of detail (LOD) processing, have suffered from their sequential execution natures. We present a GPU‐based approach which enables interactive rendering of large 3D models with hundreds of millions of triangles. Our work contributes to the massive rendering research in two ways. First, we present a simple and efficient mesh simplification algorithm towards GPU architecture. Second, we propose a novel GPU out‐of‐core approach that adopts a frame‐to‐frame coherence scheme in order to minimize the high communication cost between CPU and GPU. Our results show that the parallel algorithm of mesh simplification and the GPU out‐of‐core approach significantly improve the overall rendering performance.

Designing Experimental Methods to Predict the Expansion Ratio of EVA Foam Material and Using Finite Element Simulation to Estimate the Shoe Expansion Shape

Correcting and quickly predicting the shrink mold shape in the sport shoe industry for direct injection-expanded foam molding manufacturing procedures are critical. Traditional methods rely on the engineer to guess the initial shrink mold shape when manufacturing the actual shrink mold and shoe sole product. The artificial experience is then used to compare the original large 3D model with the shoe sole product to modify the shrink mold, requiring numerous iterations to complete. In this study, we designed a series of rectangular specimens varying with z-thickness, and measured the density in the middle location of these specimens and transferred them into an expansion ratio. Furthermore, we performed a heat transfer simulation to determine the temperature­time curve in these locations and correlated the expansion ratio with the curve. We then used the heat expansion finite element method to simulate the expansion behavior. Finally, we used the actual shoe sole to verify our algorithm; with the precision meeting the shoe sole requirement. Therefore, this algorithm can reduce the number of iterations. [doi:10.2320/matertrans.M2012178]

The geothermal project Den Haag: 3D numerical models for temperature prediction and reservoir simulation

The proposed Den Haag Zuidwest district heating system of the city of The Hague consists of a deep doublet in a Jurassic sandstone layer that is designed for a production temperature of 75 °C and a reinjection temperature of 40 °C at a flow rate of 150 m 3 h −1. The prediction of reservoir temperature and production behavior is crucial for success of the proposed geothermal doublet. This work presents the results of a study of the important geothermal and geohydrological issues for the doublet design. In the first phase of the study, the influences of the three-dimensional (3D) structures of anticlines and synclines on the temperature field were examined. A comprehensive petrophysical investigation was performed to build a large scale 3D-model of the reservoir. Several bottomhole temperatures (BHTs), as well as petrophysical logs were used to calibrate the model using thermal conductivity measurements on 50 samples from boreholes in different lithological units in the study area. Profiles and cross sections extracted from the calculated temperature field were used to study the temperature in the surrounding areas of the planned doublet. In the second phase of the project, a detailed 3D numerical reservoir model was set up, with the aim of predicting the evolution of the producer and injector temperatures, and the extent of the cooled area around the injector. The temperature model from the first phase provided the boundary conditions for the reservoir model. Hydraulic parameters for the target horizons, such as porosity and permeability, were taken from data available from the nearby exploration wells. The simulation results are encouraging as no significant thermal breakthrough is predicted. For the originally planned location of the producer, the extracted water temperature is predicted to be around 79 °C, with an almost negligible cooling in the first 50 years of production. When the producer is located shallower parts of the reservoir, the yield water temperatures is lower, starting at ≈76 °C and decreasing to ≈74 °C after 50 years of operation. This comparatively larger decrease in temperature with time is caused by the structural feature of the reservoir, namely a higher dip causes the cooler water to easily move downward. In view of the poor reservoir data, the reservoir simulation model is constructed to allow iterative updates using data assimilation during planned drilling, testing, and production phases. Measurements during an 8 h pumping test carried out in late 2010 suggest that a flow rate of 150 m 3 h −1 is achievable. Fluid temperatures of 76.5 °C were measured, which is very close to the predicted value.

Effectual Geometrical Lightweight for Large Mechanical Assemblies

Large 3D model lightweight is a practical need in CAD developments and applications. In this paper, a lightweight algorithm through intelligent geometrical information reduction for large assembly is proposed to generate simple model by using the assembly structure. This algorithm aims at reducing the size of 3D CAD model from three levels: components, feature and surfacing geometry. Key strategies such as components suppression, surface treatments based on hollow suturation and shell extraction, were used in the processing. Later experiments show that our lightweight algorithm can get satisfactory results with preferable computing performance. The lightweight technology can be widely used in many areas such as collaborative design and movement simulation, etc.

A multiresolution continuum simulation of the ductile fracture process

With the advancement in computational science that is stepping into the Exascale era and experimental techniques that enable rapid reconstruction of the 3D microstructure, quantitative microstructure simulations at an unprecedented fidelity level are giving rise to new possibilities for linking microstructure to property. This paper presents recent advances in 3D computational modeling of ductile fracture in high toughness steels. Ductile fracture involves several concurrent and mutually interactive mechanisms at multiple length scales of microstructure. With serial sectioning tomographic techniques, a digital dataset of microstructure features associated with the fracture process has been experimentally reconstructed. In this study, primary particles are accurately and explicitly modeled while the secondary particles are modeled by a two scale multiresolution continuum model. The present numerical simulation captures detailed characteristics of the fracture process, such as zigzag crack morphology, critical void growth ratios, local stress triaxiality variation, and intervoid ligament structure. For the first time, fracture toughness is linked to multiscale microstructures in a realistic large 3D model.

Semantics-driven best view of 3D shapes

The problem of automatically selecting the pose of a 3D object that corresponds to the most informative and intuitive view of the shape is known as the best view problem. In this paper we address the selection of the best view driven by the meaningful features of the shape, in order to maximize the visibility of salient components from the context or from the application point of view. Meaningful features can be automatically detected by means of semantic-oriented segmentations: we tested several approaches with very pleasant results in the automatic generation of thumbnails for large 3D model databases.