3D Mesh Model Research Articles

3D human face transplanting via depth camera

This paper presents a 3D face transplanting system with a general applicability and high efficiency. The system is capable of transplanting faces between 3D mesh models with textures quickly and simply. The main characteristic of this system is that it gets good effects on most 3D characters. This system performs face transformation and deformation with the help of the Laplace operators of the face mesh to maintain the similarity between face details. By combining Poisson image editing method and color optimization method, this system can make the texture tunes consistent and obtain a smooth transition. To make it more complete, an automatic 3D face scanning system is created to obtain 3D faces with high-quality meshes and high-resolution textures efficiently. Compared to the previous practice, the main contribution of this paper is the capability to change face transplanting objects from 2D pictures to 3D models. Moreover, the seamless connection of the two systems forms a 3D face application with a high level of automation.

Multi-Camera Active-Vision for Markerless Shape Recovery of Unknown Deforming Objects

A novel multi-camera active-vision reconfiguration method is proposed for the markerless shape recovery of unknown deforming objects. The proposed method implements a model fusion technique to obtain a complete 3D mesh-model via triangulation and a visual hull. The model is tracked using an adaptive particle filtering algorithm, yielding a deformation estimate that can, then, be used to reconfigure the cameras for improved surface visibility. The objective of reconfiguration is maximization of the total surface area visible through stereo triangulation. The surface area based objective function directly relates to maximizing the accuracy of the shape recovered, as stereo triangulation is more accurate than visual hull building when the number of viewpoints is limited. The reconfiguration process comprises workspace discretization, visibility estimation, optimal stereo-pose selection, and path planning to ensure 2D tracked feature consistency. In contrast to other reconfiguration techniques that rely on a priori known, and at times static, object models, our method focuses on a priori unknown deforming objects. The proposed method operates on-line and has been shown to outperform static-camera based systems through extensive simulations and experiments with an increased surface visibility in the presence of occluding obstacles.

Multifeature-Fitting and Shape-Adaption Algorithm for Component Repair

In recent years, the usage of additive manufacturing (AM) provides new capabilities for component repair, which includes low heat input, small heat-affected zone, and freeform near-net-shape fabrication. Because the geometry of each worn component is unique, the automated repair process is a challenging and important task. The focus of this paper is to investigate and develop a general best-fit and shape-adaption algorithm for automating alignment and defect reconstruction for component repair. The basic principle of using features for rigid-body best-fitting is analyzed and a multifeature-fitting method is proposed to best fit the 3D mesh model of a worn component and its nominal component. The multifeature-fitting algorithm in this paper couples the least-squares method and a density-based outlier detection method. These two methods run alternately to approach the best-fit result gradually and eliminate the disturbance caused from the defect geometry. The shape-adaption algorithm is used to do cross section comparison and defect reconstruction based on the best-fitted 3D model. A “point-line-surface” fracture surface detection method is proposed to construct fracture surface and the fracture surface boundary is dilated to trim the nominal 3D model to obtain defect geometry. Illustrative examples with typical components and different kinds of defects are used to demonstrate the flexibility and capability of using multifeature-fitting and shape-adaption algorithm developed in this paper.

A robust 3D mesh watermarking algorithm utilizing fuzzy C-Means clustering

A new robust 3D watermarking algorithm utilizing Fuzzy C-Means (FCM) clustering technique is presented. FCM clusters 3D mesh vertices into suitable and unsuitable choices to insert the watermark without occasioning visible deformation, and also it is tough for the attacker to determine places of the watermark insertion. Two watermarking processes are offered to insert the watermark into 3D mesh models. The first process utilizes topical statistical measurements like average and standard deviation in order to alter the values of vertices to secret watermark data into 3D mesh models, however, the second process utilizes a jumbled insertion planning to insert the watermark inside 3D mesh models utilizing the topical statistical measurements and altering 3D mesh vertices together. Simulation results show that the proposed algorithm is robust. The watermarked 3D mesh models are resistant to several attacks like similarity transforms, noise addition, cropping and mesh smoothing.

Blind 3D Mesh Watermarking for 3D Printed Model by Analyzing Layering Artifact

Because they will impact so many areas, copyright issues will inevitably arise as 3D printing expands into the content industry. The problem is that protections based on conventional methods are not effective, because the 3D printing process disables those protections. In this paper, we propose a robust and blind watermarking scheme that is able to protect content not only when the 3D model is shared in the digital world, but also when the 3D digital content is converted to analog content by 3D printing. First, we base our proposed watermark on a component that is unchanging to the printing direction for robustness against the printing process. The printing artifacts, instead of being regarded as severe distortion, are treated as a template that provides orientation information to the watermark detector. To achieve this, we also propose a blind estimation algorithm for the printing direction that starts from an analysis of the layering artifact. Using the results from a proposed estimator, the watermark from the printed-and-scanned model is synchronized with the original orientation. With the results of our tests with various 3D mesh models and attacks, we experimentally verified that the proposed method does not lose embedded patterns during the 3D print-scan process, especially with low-cost printers. Moreover, our method provides a new solution for estimating the printing direction that will be useful in a variety of fields.

An integrated Terrestrial Laser Scanner (TLS), Deviation Analysis (DA) and Finite Element (FE) approach for health assessment of historical structures. A minaret case study

This paper presents a multi-disciplinary approach for identification of historic buildings structural health with combination of Terrestrial Laser Scanning (TLS) survey, Deviation Analysis (DA) and Finite Element (FE) numerical modelling. The proposed methodology was discussed through the application to an illustrative case study: an early medieval period brick minaret (Eğri Minaret) located in Aksaray (central Turkey). After standing upright for several centuries, the minaret has developed tilt, and today the structure is supported with steel cables. Precise direction of inclination, leaning angle, local deviations from circular building shape, deflections from vertical planes, local curvatures and related maps were obtained with high accuracy by DA, based on detailed point cloud 3D mesh model. Differently from traditional approaches in FE analysis, the paper discusses a method for direct transfer of high accuracy TLS based 3D model to FE structural analysis software, subsequently employed to interpret and verify structural health of the historic building. Through the discussion of the results, it can be considered that the integration of these different techniques (being the whole process non-destructive, effective and expeditious for surface analysis) is a promising methodology for health assessment and analysis of historic constructions.

Extending VTK library to dynamically modify polygonal meshes in medical applications

Rising reverse engineering applications require the use of 3D models based on polygonal meshes and a set of modeling operations to shape the final product. Usually, 3D modeling tools do not exploit existing software development kits for developing custom virtual applications. This approach can be very useful for reverse engineering process in the medical field. The paper describes the software development of local mesh modeling algorithms as an extension of the open source library VTK with the aim of shaping 3D triangulated meshes. Then, a case study has been considered to create virtual modeling tools supporting the design process of custom-fit products and, in particular, of lower limb prosthetic socket for amputees. The application has been tested to design a socket for a patient with an above knee amputation. Results reached so far provide a positive feedback on the quality of the designed process and outcome, mainly thanks to the use of the virtual tools based on the developed software modules for 3D mesh modeling.

Use of photo-based 3D photogrammetry in analysing the results of laboratory pressure grouting tests

This paper presents a non-destructive, low-cost, photo-based, 3D reconstruction technique for characterizing geo-materials with irregular shapes of a relatively large size. After being validated against two traditional volume measurement methods, namely the vernier caliper method and the fluid displacement method for regular and irregular shapes, respectively, 3D photogrammetry was used to analyse the grout bulbs formed in laboratory pressure grouting tests. The reconstructed 3D mesh model of the sample provides accurate and detailed 3D vertex data, which allowed the volume, densification efficiency and bleeding behaviour of the grout bulbs to be analysed. Comparing the bulb section views at different grouting pressures also offers an intuitive observation of the grout development and propagation process. Moreover, the 3D vertex data and surface area included in the model are of great importance in validating numerical predictions of the pressure grouting process and analysing the interface shear resistance of grouted soil nails or anchors. Compared to existing approaches, the new 3D photogrammetry method possesses several key advantages: (a) it does not require expensive, specialized equipment; (b) samples are not destroyed or modified during testing; (c) it allows to reconstruct objects of various scales and (d) the software is public domain. Therefore, the adoption of this 3D photogrammetry method will facilitate research in the pressure grouting process and can be extended to other problems in geotechnical engineering.

MACHINE LEARNING OF THREE-DIMENSIONAL LEFT VENTRICULAR DEFORMATION FOR AUTOMATED DIAGNOSTIC SUPPORT IN AMYLOID, FABRY, AND HYPERTROPHIC CARDIOMYOPATHY: A CARDIOVASCULAR MRI IMAGING STUDY

Cardiac Magnetic Resonance (CMR) is considered a reference standard diagnostic tool for the evaluation of cardiomyopathy, and is frequently used to differentiate cause of left ventricular hypertrophy (LVH). The capacity to differentiate etiology based upon myocardial deformation alone is particularly attractive when contrast is contraindicated. 3-dimensional (3D) feature tracking allows for spatial mapping of both conventional (radial, circumferential and longitudinal) and principal strain markers from routine, non-contrast 2D cine images. In this study, we investigated the potential of this analysis approach to differentiate the cause of LVH in patients with confirmed cardiomyopathies associated with Left Ventricular Hypertrophy (LVH): Hypertrophic cardiomyopathy (HCM), Fabry cardiomyopathy, and cardiac amyloidosis (CA). Forty-five subjects were recruited with confirmed LVH and a known cardiomyopathy state (HCM, N=15; Fabry, N=15; Cardiac Amyloid, N=15). All cardiomyopathy states were confirmed by published CMR criteria (HCM and CA) and/or genetic testing (Fabry and HCM). CMR imaging was performed at 3T using a standardized protocol inclusive of multi-planar cine imaging. LV ejection fraction (LVEF) was quantified using commercially available software (cvi42, Circle Cardiovascular Imaging Inc.). 3D strain analysis was performed using custom in-house software (GIUSEPPE) with generation of endocardial, epicardial and transmural spatial strain maps using a dynamic 3D mesh model. Principal component analysis was performed (Matlab, MathWorks) on the amplitude of peak-systolic strain obtained in all AHA segments in both conventional (longitudinal, circumferential, radial) and principal directions. The mean age was 57.9±15.2 years with 17 (37%) female. The respective LVEFs were 57.9±13.6%, 69.1±6.1%, and 69.5±9.8% among CA, Fabry’s, and HCM, respectively. 3D strain distributions were successfully computed for all patients. Segmental strain amplitude measures were subjected to principal component analysis. The first and second principal components of the regional strain data were used as a diagnostic marker by means of a Naive Bayes classifier. Both the posterior predictive distribution and the classification probability were visualized (Figure 1), showing capacity for disease state discrimination. The confusion matrix revealed an overall accuracy of 0.80, with true positive rates of 0.73 for CA, 0.8 for Fabry’s, and 0.67 for HCM. The concomitant evaluation of regional values of systolic strain amplitude in multiple directions was able to correctly classify patients by disease, based on the exclusive knowledge of regional strain amplitude patterns. These results offer strong promise for the use of 3D strain analysis to assist in the diagnosis of cardiomyopathy state among patients with LVH.

COMBINING 3D VOLUME AND MESH MODELS FOR REPRESENTING COMPLICATED HERITAGE BUILDINGS

Abstract. This study developed a simple but effective strategy to combine 3D volume and mesh models for representing complicated heritage buildings and structures. The idea is to seamlessly integrate 3D parametric or polyhedral models and mesh-based digital surfaces to generate a hybrid 3D model that can take advantages of both modeling methods. The proposed hybrid model generation framework is separated into three phases. Firstly, after acquiring or generating 3D point clouds of the target, these 3D points are partitioned into different groups. Secondly, a parametric or polyhedral model of each group is generated based on plane and surface fitting algorithms to represent the basic structure of that region. A “bare-bones” model of the target can subsequently be constructed by connecting all 3D volume element models. In the third phase, the constructed bare-bones model is used as a mask to remove points enclosed by the bare-bones model from the original point clouds. The remaining points are then connected to form 3D surface mesh patches. The boundary points of each surface patch are identified and these boundary points are projected onto the surfaces of the bare-bones model. Finally, new meshes are created to connect the projected points and original mesh boundaries to integrate the mesh surfaces with the 3D volume model. The proposed method was applied to an open-source point cloud data set and point clouds of a local historical structure. Preliminary results indicated that the reconstructed hybrid models using the proposed method can retain both fundamental 3D volume characteristics and accurate geometric appearance with fine details. The reconstructed hybrid models can also be used to represent targets in different levels of detail according to user and system requirements in different applications.

Robust watermarking scheme using Weber Law for 3D mesh models

ABSTRACTAuthentication and identification of multimedia objects play an important aspect for multimedia security. In this we present a semi-blind watermarking scheme for 3D mesh models using Weber’s law. A robust and imperceptible spectral watermarking for high rate embedding of a watermark into 3D polygonal meshes is analyzed in this paper. The proposed approach consists of these main steps (i) mesh is portioned into smaller sub-meshes, (ii) generation of watermark from the original model, (iii) watermark embedding and extraction to each sub-meshes. Extensive experimental results show an improved performance of the proposed system and also its robustness against the most common attacks including the geometric transformations, adaptive random noise, mesh smoothening, mesh cropping and combination of these attacks.

Improved Research for 3D Mesh Segmentation Based on Watershed Algorithm

Most of the 3D mesh segmentation method now is based on the curvature model. This unified error method leads to poor segmentation results. In order to solve the problem of “the unified error”, in this paper, we used the watershed algorithm. We used region growing algorithm to improve the segmentation of watershed algorithm and apply the ROI conception to achieve interest segmentation. In this method, without considering the smoothness of the split edge, the 3D mesh model can achieve their desired segmentation effect.

Sketch-based 3D object recognition from locally optimized sparse features

We propose a user-drawn sketch image-based three-dimensional (3D) object recognition method, which automatically learns and optimizes features by using unsupervised algorithm to overcome the difficulty of extracting robust features from the black and white sketch image. As a preprocessing task, both the sketch image database and the projected image database of the 3D objects are built by learning with various user-drawn sketch images and suggestive contour images of the 3D objects respectively, and each sketch image is mapped to the most similar projected database image by measuring the similarity. This enables us to avoid a direct comparison of the sketch query and the projected images of the 3D objects and to use the learned robust sparse features of the trained sketch images in the sketch database, compensating for the difference between the user-drawn sketch image and synthesized images of the 3D mesh model. The locally-enforced feature optimization of the local and global features of the database images reduces the error and retains the feature properties. Furthermore, we quantitatively compared the proposed method to previous remarkable object recognition approaches. Numerous experiments on various challenging 3D objects and sketch images demonstrate that the proposed methodology performs favorably against several state-of-the-art algorithms.

The DOM Generation and Precise Radiometric Calibration of a UAV-Mounted Miniature Snapshot Hyperspectral Imager

Hyperspectral remote sensing is used in precision agriculture to remotely and quickly acquire crop phenotype information. This paper describes the generation of a digital orthophoto map (DOM) and radiometric calibration for images taken by a miniaturized snapshot hyperspectral camera mounted on a lightweight unmanned aerial vehicle (UAV). The snapshot camera is a relatively new type of hyperspectral sensor that can acquire an image cube with one spectral and two spatial dimensions at one exposure. The images acquired by the hyperspectral snapshot camera need to be mosaicked together to produce a DOM and radiometrically calibrated before analysis. However, the spatial resolution of hyperspectral cubes is too low to mosaic the images together. Furthermore, there are no systematic radiometric calibration methods or procedures for snapshot hyperspectral images acquired from low-altitude carrier platforms. In this study, we obtained hyperspectral imagery using a snapshot hyperspectral sensor mounted on a UAV. We quantitatively evaluated the radiometric response linearity (RRL) and radiometric response variation (RRV) and proposed a method to correct the RRV effect. We then introduced a method to interpolate position and orientation system (POS) information and generate a DOM with low spatial resolution and a digital elevation model (DEM) using a 3D mesh model built from panchromatic images with high spatial resolution. The relative horizontal geometric precision of the DOM was validated by comparison with a DOM generated from a digital RGB camera. A surface crop model (CSM) was produced from the DEM, and crop height for 48 sampling plots was extracted and compared with the corresponding field-measured crop height to verify the relative precision of the DEM. Finally, we applied two absolute radiometric calibration methods to the generated DOM and verified their accuracy via comparison with spectra measured with an ASD Field Spec Pro spectrometer (Analytical Spectral Devices, Boulder, CO, USA). The DOM had high relative horizontal accuracy, and compared with the digital camera-derived DOM, spatial differences were below 0.05 m (RMSE = 0.035). The determination coefficient for a regression between DEM-derived and field-measured crop height was 0.680. The radiometric precision was 5% for bands between 500 and 945 nm, and the reflectance curve in the infrared spectral region did not decrease as in previous research. The pixel and data sizes for the DOM corresponding to a field area of approximately 85 m × 34 m were small (0.67 m and approximately 13.1 megabytes, respectively), which is convenient for data transmission, preprocessing and analysis. The proposed method for radiometric calibration and DOM generation from hyperspectral cubes can be used to yield hyperspectral imagery products for various applications, particularly precision agriculture.

USE OF VERTICAL AERIAL IMAGES FOR SEMI-OBLIQUE MAPPING

Abstract. The paper proposes a methodology for the use of the oblique sections of images from large-format photogrammetric cameras, by exploiting the effect of the central perspective geometry in the lateral parts of the nadir images (“semi-oblique” images). The point of origin of the investigation was the execution of a photogrammetric flight over Norcia (Italy), which was seriously damaged after the earthquake of 30/10/2016. Contrary to the original plan of oblique acquisitions, the flight was executed on 15/11/2017 using an UltraCam Eagle camera with focal length 80 mm, and combining two flight plans, rotated by 90º (“crisscross” flight). The images (GSD 5 cm) were used to extract a 2.5D DSM cloud, sampled to a XY-grid size of 2 GSD, a 3D point clouds with a mean spatial resolution of 1 GSD and a 3D mesh model at a resolution of 10 cm of the historic centre of Norcia for a quantitative assessment of the damages. From the acquired nadir images the “semi-oblique” images (forward, backward, left and right views) could be extracted and processed in a modified version of GEOBLY software for measurements and restitution purposes. The potential of such semi-oblique image acquisitions from nadir-view cameras is hereafter shown and commented.

APPROACH TO 3D ANALYSIS OF GRAVITY PTOSIS

Abstract. The assessment of ptosis degree for rejuvenation procedures, the choice of following operation technique and evaluation of surgery result are based on subjective visual examination and surgeon’s experience. The photogrammetric scans of 25 female patients of age 20 to 55 in vertical and supine (horizontal) position of body with placing the regular marker points on the face were analyzed. For 5 patients, also the CT data was acquired and segmentation of soft tissue was performed. Four of these patients underwent SMAS-lifting, the photogrammetry scanning was repeat 6 months after the operation. Computer vision algorithms was used for markers detection on the 3D model texture, marker were projected from texture to triangular mesh. 3D mesh models were registered with user defined anatomy points and pair selection based on markers location was done. Pairs of points on vertical and horizontal 3D models were analyzed for surface tissue mobility examination. The migration vectors of each side of the face are uniformly directed upwards and laterally. The vectors are projected at the areas of so-called ligaments demonstrate no evidence in deviation from row sequences. The volume migration is strongly correlates with the age of examined patients, on the contrary the point migration moderately correlates with age in patients of 30 to 50 years old. The analysis of migration vectors before and after the SMAS-lifting revealed no significant changes in surface points’ migration. The described method allows to assess the mechanical conditions of individual face and evaluate efficacy of surgery. This approach can be used for the classification of face ptosis grade.

Numerical simulation of multi-pass GTA welding of grade 91 steel

A thermo-mechanical analysis of multi-pass GTA welding of 6mm thick Grade 91 steel plate was carried out using three different models which include a 2D model, a 3D coarse meshed model and a 3D fine meshed model. Predicted thermal cycles, residual stresses and distortion were validated using experimental tools. Effect of preheat employed between weld passes on distortion was simulated and also experimentally validated. Good correlation was obtained between experimental results and those predicted from the simulation for 3D fine meshed model. Distortion analysis carried out using the above model considering phase transformation effect and employing large distortion theory predicted distortion values very close to that of the actual values. For simulating preheat, a circular disc shaped heat source and for simulating GTA welding, a double ellipsoid heat source model were employed. Experimental and FEM results show that preheating up to 200°C reduced the distortion of Grade 91 steel plate considerably during multi-pass welding.

A zero-watermarking scheme for three-dimensional mesh models based on multi-features

The aim of this study is to devise a zero-watermarking algorithm, the main challenge of which is the selection and construction of resilient features of three-dimensional(3D) models while improving the resilience of the zero-watermarking algorithm to common attacks. A novel zero-watermarking scheme for 3D mesh models based on multi-features is proposed in this paper. Using the Ordered Statistics Vertex Extraction and Tracing Algorithm, the stable vertices of a 3D model are determined. Then, the skewness measure of the shape diameter function values and vertex norms of the stable vertices are determined. Combined with the distribution feature of the number of stable vertices, a resilient watermark is applied. Experimental results show that the proposed scheme is not affected by a similarity transformation (such as translation, rotation, or uniform scaling) or vertex reordering. The scheme is also sufficiently resilient to noise, simplification, smoothing, and subdivision attacks. In addition, the scheme can resist cropping to a certain extent. The scheme proposed in this paper is suitable for applications that require 3D models with a higher accuracy and that cannot be embedded with a watermark that would modify the data of those models.

Large Mine Hoist Drum Topology Optimization Design

According to the 2JK type large mine hoist drum manhole, surrounding the shell cracks problems from time to time, based on the conceptual design principle of variable density topology optimization, integrated use of OptiStruct, HyperMesh software functional modules to build a 3D mesh model of the drum. Analyze its finite static element, confirm its weaknesses, then adjust the structure through topology optimization design. Ensure safe operation under normal operating conditions. The optimization design results show that, Static analysis results roughly keep fit with the hoist drum troubleshooting, the maximum stress of surroundings decreased by nearly 38.46% after structural topology optimization, distribution is more uniform, quality dropped by 5.7%, reaching the purpose of lightweight. In this paper, research methods and conclusions provide a viable reference for corporate design departments to solve the problem of drum cracking.

Geometric modeling of hepatic arteries in 3D ultrasound with unsupervised MRA fusion during liver interventions.

Modulating the chemotherapy injection rate with regard to blood flow velocities in the tumor-feeding arteries during intra-arterial therapies may help improve liver tumor targeting while decreasing systemic exposure. These velocities can be obtained noninvasively using Doppler ultrasound (US). However, small vessels situated in the liver are difficult to identify and follow in US. We propose a multimodal fusion approach that non-rigidly registers a 3D geometric mesh model of the hepatic arteries obtained from preoperative MR angiography (MRA) acquisitions with intra-operative 3D US imaging. The proposed fusion tool integrates 3 imaging modalities: an arterial MRA, a portal phase MRA and an intra-operative 3D US. Preoperatively, the arterial phase MRA is used to generate a 3D model of the hepatic arteries, which is then non-rigidly co-registered with the portal phase MRA. Once the intra-operative 3D US is acquired, we register it with the portal MRA using a vessel-based rigid initialization followed by a non-rigid registration using an image-based metric based on linear correlation of linear combination. Using the combined non-rigid transformation matrices, the 3D mesh model is fused with the 3D US. 3D US and multi-phase MRA images acquired from 10 porcine models were used to test the performance of the proposed fusion tool. Unimodal registration of the MRA phases yielded a target registration error (TRE) of [Formula: see text]mm. Initial rigid alignment of the portal MRA and 3D US yielded a mean TRE of [Formula: see text]mm, which was significantly reduced to [Formula: see text]mm ([Formula: see text]) after affine image-based registration. The following deformable registration step allowed for further decrease of the mean TRE to [Formula: see text]mm. The proposed tool could facilitate visualization and localization of these vessels when using 3D US intra-operatively for either intravascular or percutaneous interventions to avoid vessel perforation.