3D Mesh Model Research Articles

Repairing man-made meshes via visual driven global optimization with minimum intrusion

3D mesh models created by human users and shared through online platforms and datasets flourish recently. While the creators generally have spent large efforts in modeling the visually appealing shapes with both large scale structures and intricate details, a majority of the meshes are unfortunately flawed in terms of having duplicate faces, mis-oriented regions, disconnected patches, etc., due to multiple factors involving both human errors and software inconsistencies. All these artifacts have severely limited the possible low-level and high-level processing tasks that can be applied to the rich datasets. In this work, we present a novel approach to fix these man-made meshes such that the outputs are guaranteed to be oriented manifold meshes that preserve the original structures, big and small, as much as possible. Our key observation is that the models all visually look meaningful, which leads to our strategy of repairing the flaws while always preserving the visual quality. We apply local refinements and removals only where necessary to achieve minimal intrusion of the original meshes, and global adjustments through robust optimization to ensure the outputs are valid manifold meshes with optimal connections. We test the approach on large-scale 3D datasets, and obtain quality meshes that are more readily usable for further geometry processing tasks.

A Robust Algorithm to Remove the Self-intersection of 3D Mesh Data without Changing the Original Shape

Self-intersection is a serious problem in computational geometry and digital manufacturing. Because intersected parts do not exist in the physical world, the self-intersection must be removed for actually applications such as 3D printing or CNC machining. In the conventional method, such intersected parts are usually deleted, which causes the change of the original shape. In this research, a robust algorithm to remove the self-intersection of 3D mesh model is proposed. It could automatically detect the self-intersection, and remove the self-intersection without changing the original shape. The proposed algorithm has four steps. (1) Detect the intersected facets in the mesh model. (2) Divide the intersected facets along the crossing lines. (3) Find the outside facets. (4) Delete the inner facets and burying facets. Different models are used to do experiments, and the experimental results prove the validity and practicability of the proposed algorithm.

Geometric Evaluation of Mobile-Phone Camera Images for 3D Information

This study aimed to investigate the usability of smartphone camera images in 3D positioning applications with photogrammetric techniques. These investigations were performed in two stages. In the first stage, the cameras of five smartphones and a digital compact camera were calibrated using a calibration reference object, with signalized points having known three-dimensional (3D) coordinates. In the calibration process, the self-calibration bundle adjustment method was used. To evaluate the metric performances, the geometric accuracy tests in the image and object spaces were performed and the test results were compared. In the second stage, a 3D mesh model of a historical cylindrical structure (height = 8 m and diameter = 5 m) was generated using Structure-from-Motion and Multi-View-Stereo (SfM-MVS) approach. The images were captured using the Galaxy S4 smartphone camera, which produced the best result in the geometric accuracy tests for smartphone cameras. The accuracy tests on the generated 3D model were also applied in order to examine 3D object reconstruction capabilities of imaging with this device. The results demonstrated that smartphone cameras can be easily used as image acquisition tools for multiple photogrammetric applications.

Thermomechanical Analysis of A-TIG and MP-TIG Welding of 2.25Cr-1Mo Steel Considering Phase Transformation

In the present study, a finite element-based 3D mesh model is used to simulate the effect of welding processes on the temperature distribution, residual stress and distortion in 11-mm-thick 2.25Cr-1Mo steel weld joints. Tungsten inert gas (TIG) and activated-TIG (A-TIG) welding processes were employed for the fabrication of weld joints. Austenite-to-bainite phase transformation is taken into account in the numerical analysis. The heat input fitting tool has been used to calibrate the heat source by matching the simulated weld bead with that of the actual weld bead. Peak temperature was higher at the weld center for A-TIG weld joint, and the weld joint exhibited a sharp temperature gradient at the weld interface. There was good agreement between the predicted and measured thermal cycles. A-TIG and multipass-TIG (MP-TIG) weld joints exhibited similar longitudinal residual stresses in heat affected zone with a difference of 50 MPa. Moreover, A-TIG weld joint fabricated by double-side welding technique employing two passes exhibited reduced distortion than MP-TIG weld joints. A higher magnitude of distortion was in MP-TIG weld joint which was attributed to more weld metal volume caused by more number of weld passes required to fill the V-groove. There was good agreement between the predicted and measured residual stress and distortion values.

An asymmetric and optimized encryption method to protect the confidentiality of 3D mesh model

3D models are widely used in computer graphics, design and manufacture engineering, art animation and entertainment. With the universal of acquisition equipment and sensors, a huge number of 3D models are generated, which are becoming the major source of engineering data. How to preserve the privacy of the 3D models is a challenge issue. In this paper, an asymmetric and optimized encryption method is presented to protect the 3D mesh models. Firstly, we propose an asymmetric encryption method for 3D mesh models to overcome the drawbacks of traditional symmetric encryption. The primary benefit is that our approach can enhance the security of the key. Secondly, we extend the typically asymmetric encryption algorithm from integer domain to float domain. In our method, we present a normalization function to map the float DC (Discrete Cosine) coefficients to integer domain. Thirdly, considering that the shape error and encryption/decryption computation cost are contradictory in the normalization mapping, we formulate the contradiction as a multi-objective optimization problem. And then, we propose a multi-objective solution to find an optimized mapping range for encryption/decryption efficiently. Furthermore, benefiting from the proposed asymmetric encryption framework, we continue to put forward a method to check the integrity of the encrypted 3D mesh model, in which the digest is encrypted twice to generate digital signature more safely. The proposed method has been tested on 3D mesh models from Stanford university and other sources to demonstrate the effect of the proposed encryption method and optimization mechanism.

3D non-conforming mesh model for flow in fractured porous media using Lagrange multipliers

This work presents a modeling approach for single-phase flow in 3D fractured porous media with non-conforming meshes. To this end, a Lagrange multiplier method is combined with a parallel variational transfer approach. This Lagrange multiplier method enables the use of non-conforming meshes and depicts the variable coupling between fracture and matrix domain. The variational transfer allows general, accurate, and parallel projection of variables between non-conforming meshes (i.e. between fracture and matrix domain). Comparisons of simulations with 2D benchmarks show good agreement, and the applied finite element Lagrange multiplier spaces show good performance. The method is further evaluated on 3D fracture networks by comparing it to results from conforming mesh simulations which were used as a reference. Application to realistic fracture networks with hundreds of fractures is demonstrated. Mesh size and mesh convergence are investigated for benchmark cases and 3D fracture network applications. Results demonstrate that the Lagrange multiplier method, in combination with the variational transfer approach, is capable of modeling single-phase flow through realistic 3D fracture networks.

Efficient and realistic character animation through analytical physics-based skin deformation

Physics-based skin deformation methods can greatly improve the realism of character animation, but require non-trivial training, intensive manual intervention, and heavy numerical calculations. Due to these limitations, it is generally time-consuming to implement them, and difficult to achieve a high runtime efficiency. In order to tackle the above limitations caused by numerical calculations of physics-based skin deformation, we propose a simple and efficient analytical approach for physics-based skin deformations. Specifically, we (1) employ Fourier series to convert 3D mesh models into continuous parametric representations through a conversion algorithm, which largely reduces data size and computing time but still keeps high realism, (2) introduce a partial differential equation (PDE)-based skin deformation model and successfully obtain the first analytical solution to physics-based skin deformations which overcomes the limitations of numerical calculations. Our approach is easy to use, highly efficient, and capable to create physically realistic skin deformations.

Precise delineation and tumor localization based on novel image registration strategy between optical coherence tomography and computed tomography in the radiotherapy of intraocular cancer

Radiation-associated toxicities due to sophisticated ocular anatomy and shape variability of organs at risk (OARs) are major concerns during external beam radiation therapy (EBRT) of patients with intraocular cancer. A novel two-step image registration strategy between optical coherence tomography (OCT) and computed tomography (CT) images was proposed and validated to precisely localize the target in the EBRT of patients with intraocular cancer. Specifically, multiple features from OCT and CT images were extracted automatically, then spatial transformation based on thin-plate spline function was performed iteratively to achieve feature alignment between the CT and OCT images. Finally, an exclusive OR (XOR) algorithm was applied for precise 3D registration using a 3D-mesh model generated from OCT and CT volumes. The accuracy of the proposed novel registration strategy was validated and tested in a schematic-eye phantom with an artificially introduced tumor and in ten patients with confirmed primary and/or secondary intraocular cancer. There was an average registration error and computational time of 0.21 ± 0.05° and 259 ± 5 s, together with an average Dice similarity coefficient and Hausdorff distance of 88.4 ± 0.65 and 0.89 ± 0.09, respectively. The preliminary experimental results demonstrated that the proposed novel strategy to overcome current limitations on eye modeling and to localize precisely the tumor target during EBRT of intraocular cancer is promising.

Mesh-based camera pairs selection and occlusion-aware masking for mesh refinement

Many Multi-View-Stereo algorithms extract a 3D mesh model of a scene, after fusing depth maps into a volumetric representation of the space. Due to the limited scalability of such representations, the estimated model does not capture fine details of the scene. Therefore a mesh refinement algorithm is usually applied; it improves the mesh resolution and accuracy by minimizing the photometric error induced by the 3D model into pairs of cameras. The choice of these pairs significantly affects the quality of the refinement and usually relies on sparse 3D points belonging to the surface. Instead, in this paper, to increase the quality of pairs selection, we exploit the 3D model (before the refinement) to compute five metrics: scene coverage, mutual image overlap, image resolution, camera parallax, and a new symmetry term. To improve the refinement robustness, we also propose an explicit method to manage occlusions, which may negatively affect the computation of the photometric error. The proposed method takes into account the depth of the model while computing the similarity measure and its gradient. We quantitatively and qualitatively validated our approach on publicly available datasets against state of the art reconstruction methods.

Three-dimensional analysis of mandibular functional units in adult patients with unilateral posterior crossbite: A cone beam study with the use of mirroring and surface-to-surface matching techniques.

To use three-dimensional (3D) mirroring and surface-to-surface techniques to determine any differences in mandibular functional unit shape and morphology between the crossbite side and non-crossbite side in adult patients with posterior unilateral crossbite who had not received any corrective treatment for malocclusion. Cone-beam computed tomography (CBCT) records from 24 consecutive adult white patients (mean age, 27.5 years; range 22.6-39.7 years; 14 women and 10 men) seeking treatment for maxillary transverse deficiency were assessed in this study. The control group comprised CBCT scans from age- and sex-matched patients. Segmentation masks were generated to obtain 3D surface mesh models of the mandibles and analyze the six skeletal functional units, which were further analyzed with reverse engineering software. Statistically significant differences in the mean surface distance when comparing the study sample and the control sample were found at the condylar process, mandibular ramus, angular process (P ≤ .0001), and alveolar process (P ≤ .01); no statistically significant differences were found for the coronoid process, the chin, and the mandibular body (P ≥ .5). The condylar, angular, and alveolar processes plus the mandibular ramus appear to play a more dominant role than did the body, the coronoid, and the chin units in the asymmetry of the mandible in patients with unilateral crossbite.

Progressive sketching with instant previewing

Sketch-based modeling uses freeform strokes as basic modeling metaphor and the modeling process typically involves two phases: sketching and sculpting. This paper presents a method to enhance the sketching phase to have the features of both sketching and sculpting. The key idea of the method is progressive sketching with instant previewing, which has the capacity of intuitively creating complex initial shapes that interpolate all the sketched strokes. The process lets the user iteratively sketch and meanwhile updates the reconstructed 3D shape instantly, which enables the user to be aware of the up-to-date shape. The underlying technique supporting this process is a novel surface construction algorithm that produces 3D triangular mesh models typically with only a single connected component and gradual shape changes during iterative sketching as well. To demonstrate the capability of the method, a sketching-based modeling prototype is also developed, which includes both sketching and sculpting functions. Experiments show that the proposed method can allow users to intuitively and flexibly create and edit 3D models even with complex topology, which is usually difficult for conventional sketch-based modeling systems.

A Multi-View Texture Fusion Approach for High Quality 3D Face Modelling

This paper presents an accurate means for the 3D face texture mapping based on a multiple-view 3D scanning system. Given a reconstructed 3D mesh model and a set of calibrated images, a high-quality texture mosaic of the surface can be created by the proposed method. The proposed method aims to avoid noticeable seams, color discontinuity and ghosting problems. The method performs in two steps, i.e. occlusion areas filtering and the fusion of different texture images. The filtering is performed to identity invisible areas from the camera viewpoint and leaves them not textured. To perform the occluded areas filtering, we combine the geometrical features of the objects and the visual range of the camera. Experimental results showed that, texture mapping quality and precision can be improved in comparison with conventional means.

Laplacian-based 3D mesh simplification with feature preservation

We propose a novel Laplacian-based algorithm that simplifies triangle surface meshes and can provide different preservation ratios of geometric features. Our efficient and fast algorithm uses a 3D mesh model as input and initially detects geometric features by using a Laplacian-based shape descriptor (L-descriptor). The algorithm further performs an optimized clustering approach that combines a Laplacian operator with K-means clustering algorithm to perform vertex classification. Moreover, we introduce a Laplacian weighted cost function based on L-descriptor to perform feature weighting and error statistics comparison, which are further used to change the deletion order of the model elements and preserve the saliency features. Our algorithm can provide different preservation ratios of geometric features and may be extended to handle arbitrary mesh topologies. Our experiments on a variety of 3D surface meshes demonstrate the advantages of our algorithm in terms of improving accuracy and applicability, and preserving saliency geometric features.

A Distributed Plasticity Approach for Steel Frames Analysis Including Strain Hardening Effects

This paper focuses on the creation and numerical application of physically nonlinear plane steel frames analysis problems. The frames are analysed using finite elements with axial and bending deformations taken into account. Two nonlinear physical models are used and compared – linear hardening and ideal elastic-plastic. In the first model, distributions of plastic deformations along the elements and across the sections are taken into account. The proposed method allows for an exact determination of the stress-strain state of a rectangular section subjected to an arbitrary combination of bending moment and axial force. Development of plastic deformations in time and distribution along the length of elements are determined by dividing the structure (and loading) into the parts (increments) and determining the reduced modulus of elasticity for every part. The plastic hinge concept is used for the analysis based on the ideal elastic-plastic model. The created calculation algorithms have been fully implemented in a computer program. The numerical results of the two problems are presented in detail. Besides the stress-strain analysis, the described examples demonstrate how the accuracy of the results depends on the number of finite elements, on the number of load increments and on the physical material model. COMSOL finite element analysis software was used to compare the presented 1D FEM methodology to the 3D FEM mesh model analysis.

Mapping invasive plant with UAV-derived 3D mesh model in mountain area—A case study in Shenzhen Coast, China

Invasive plants constitute one of the major causes of biodiversity loss, and its monitoring plays an important role in the management of coastal ecological systems. This study aimed to apply high precision 3D mesh-model and digital orthophoto map (DOM) derived from unmanned aerial vehicle (UAV) multi view images to monitor the invasive plants over coastal mountain region in Shenzhen, China. To overcome the limitations of RGB images, the Gray-level Co-occurrence Matrix (GLCM) features of images were analyzed and combined with spectral features to obtain the 2-dimentional distribution of invasive plants first, using an object-based image analysis technique. A fine analysis was then introduced to obtain a more accurate 3-dimentional distribution of invasive plant by combining 2-dimentional distribution of invasive plant and 3D mesh model. the results have shown that: (1) Although the UAV RGB image has limited spectral information, the low-altitude makes the spatial resolution very high, which can effectively enhance the effectiveness of the texture in mapping invasive plants, and finally achieved an overall accuracy of 93.25%. (2) The use of 3D mesh model, on the one hand, could significantly alleviate the impact of undulatory terrain over mountain area and improve the classification result; on the other hand, it could better visualize the final results, helping us more intuitively understanding the distribution of invasive plants. This study demonstrated the great potential of UAV-derived 3D mesh model in accurate natural resource management over mountain areas.

Improved 3D Scene Modeling for Image Registration in Change Detection

This paper presents a novel method for 3D scene modeling using stereo vision, with an application to image registration. The method constists of two steps. First, disparity estimates are refined, by filling gaps of invalid disparity and removing halos of incorrectly assigned disparity. A coarse segmentation is obtained by identifying depth slices, after which objects are clustered based on color and texture information using Gabor filters. The second step consists of reconstructing the resulting objects in 3D for scene alignment by fitting a planar region. A 2D triangle mesh is generated, and a 3D mesh model is obtained by projecting each triangle onto the fitted plane. Both of these extensions result in improved alignment quality with respect to the state of the art, and operate in near real time using multi-threading. As a bonus, the refined disparity map can also be used in combination with the existing method.

A reversible and affine invariant 3D data hiding technique based on difference shifting and logistic map

Image steganography has evolved as an active area of research because of its advantage to hide secret information inside an ingenuous image invisibly. In the recent years, improvements have been done in hardware to process 3D image models which laid down the path for 3D image steganography. The proposed work presents a novel approach of reversible data hiding in 3D mesh models. Difference between the vertices is shifted to hide secret bits inside the vertices. Chaotic logistic map is also used in the proposed work to decide the coordinate taken up for embedding. The proposed blind steganography system withstands rotation, scaling and translation attacks. Novel mesh traversal algorithm is proposed to visit the mesh vertices. This algorithm gives a unique mesh traversal algorithm for every 3D mesh model. The performance of proposed approach is compared with three well-known image steganography approaches over five cover models. The experimental results reveal that the difference between stego model and cover model cannot be observed by human eye. The proposed approach provides better embedding capacity than the previous approach in the field of reversible data hiding in 3D cover models.

Real-time 3D reconstruction method using massive multi-sensor data analysis and fusion

This paper proposes a method to reconstruct three-dimensional (3D) objects using real-time fusion and analysis of multiple sensor data. This paper attempts to create a realistic 3D visualization with which a remote pilot can intuitively control a remote unmanned robot by utilizing the characteristics of massive sensor data. The 3D reconstruction system proposed in this paper is comprised of 3D and two-dimensional (2D) data segmentation method, a 3D reconstruction method applied to each object, and a projective texture mapping method. Specifically, we propose applying both a 2D region extraction method and a 3D mesh modeling method to each object. The proposed schemes are implemented as a real-time application to verify real-time performance. This paper proves that 3D meshes can be modeled in real time by using the proposed method. The proposed method allows the remote control of a robot for real-time 3D rendering of remote scenes, which is essential for various tasks in areas that cannot be easily accessed by humans.

Analysis Image-Based Automated 3D Crack Detection for Post-disaster Bridge Assessment in Flyover Mall Boemi Kedaton

Recovery efforts following a disaster can be slow and painstaking work, and potentially put responders in harm's way. A system which helps identify defects in critical building elements (e.g., concrete columns) before responders must enter a structure can save lives. In this paper we propose a system, centered around an image based three-dimensional (3D) reconstruction method and a new 3D crack detection algorithm. The image-based method is capable of detecting and analyzing surface damages in 3D. We also demonstrate how the robotics can be used to gather the images from which the reconstruction is created, further reducing the risk to responders. In this regard, image-based 3D reconstructions represent a convenient method of creating 3D models because most robotic platforms can carry a lightweight camera payload. Additionally, the proposed 3D crack detection algorithm also provides the advantage of being able to operate on 3D mesh models regardless of their data collection source. Our experimental results show that 3D crack detection algorithm performs well constructions, successfully identifying cracks, reconstructing 3D profiles, and measuring geometrical characteristics on damaged elements and not finding any cracks on intact ones.

A Fast 3D Brain Extraction and Visualization Framework Using Active Contour and Modern OpenGL Pipelines

Brain extraction is a process of removing non-brain tissue in the brain magnetic resonance (MR) images and serves as a first step towards more delicate brain segmentation. Although many brain extraction methods have been proposed in the literature, most of them are either laborious or time consuming, and lack of instant visualization. This leads to a time lag between image acquisition and comprehensive visualization. Especially for intraoperative image based neurosurgery navigation, the time lag from image acquisition to brain visualization should be reduced as much as possible. In this paper, we propose an end-to-end fast brain extraction and visualization framework. The input is a T1-weighted MR volume and the output is comprehensive brain visualization. An improved brain extraction tool (BET) algorithm is proposed to evolve a 3D active mesh model to fit the brain surface in the 3D image. Then the brain mask is generated per slice using a polygon fill algorithm. At last, a ray-casting volume rendering algorithm is used to visualize the brain surface with the help of the generated mask. All the operations are performed using the modern OpenGL pipelines running on a graphics processing unit (GPU). Experiments were performed on two publicly available datasets and one clinical dataset to compare our method with five state-of-the-art methods including the original BET in terms of segmentation accuracy and time cost. Our method achieved mean Dice coefficients of 96.8%, 97.1%, 98.5% and mean time cost of 361 ms, 341 ms, 502 ms on the three datasets, outperforming all the other methods.