Template Mesh Research Articles

Image-Aligned Dynamic Liver Reconstruction Using Intra-Operative Field of Views for Minimal Invasive Surgery.

During hepatic minimal invasive surgery (MIS), 3-D reconstruction of a liver surface by interpreting the geometry of its soft tissues is achieving attractions. One of the major issues to be addressed in MIS is liver deformation. Moreover, it severely inhibits free sight and dexterity of tissue manipulation, which causes its intra-operative morphology and soft tissue motion altered as compared to its pre-operative shape. While many applications focus on 3-D reconstruction of rigid or semi-rigid scenes, the techniques applied in hepatic MIS must be able to cope with a dynamic and deformable environment. We propose an efficient technique for liver surface reconstruction based on the structure from motion to handle liver deformation. The reconstructed liver will assist surgeons to visualize liver surface more efficiently with better depth perception. We use the intra-operative field of views to generate 3-D template mesh from a dense keypoint cloud. We estimate liver deformation by finding best correspondence between 3-D templates and reconstruct a liver image to calculate translation and rotational motions. Our technique then finely tunes deformed surface by adding smoothness using shading cues. Up till now, this technique is not used for solving the human liver deformation problem. Our approach is tested and validated with synthetic as well as real in vivo data, which reveal that the reconstruction accuracy can be enhanced using our approach even in challenging laparoscopic environments.

A parametric morphing method for generating structured meshes for marine free surface flow applications with plane symmetry

Abstract This article introduces a method for morphing a parametric, rectangular and structured 3D template mesh such that it embodies: (1) a given (half) hull surface properly aligned with a pre-defined air-water interface zone, (2) a high-quality boundary layer region near the hull, and (3) a smooth transition of the mesh to the template mesh structure away from the hull. The performance of the proposed method is successfully validated on three widely studied benchmark cases, namely the parabolic Wigley hull, the Series 60 hull and the DTMB 5415 combatant hull. The proposed automated mesh generation method is useful in shape optimization for computational fluid dynamics, among others. Highlights A new method for creating structured meshes for marine CFD applications is presented. The proposed method is parametric and thus fully programmable. The method includes an automatic resolution of CAD geometry errors. The resulting meshes are strictly orthogonal near the inter-phase zone and the hull. The main application of the proposed method is in CFD-based shape optimization.

Foot Measurement Using 3D Scanning Model

In a three-dimensional (3D) foot scanning, a 3D point cloud is generated and meshed to create a 3D foot model with depth information. In the previous analog process of foot scanning is to draw an outline of the foot and imitate the foot directly. This method has some disadvantage that has a measurement error, difficult to recreate, inaccuracy of reference point and an error by an expert abilities. In this paper, in-plane deformation measurement method is proposed to solve this problem. In-plane deformation measurement method is a novel method to measure foot size from a 3D foot scanning data. The Shrink-Wrap method is used to reconstruct a foot model, that estimate the foot model by wrapping the surface of a foot of the square template mesh model. For comparison, foot length, foot width and height of the instep is measured with the proposed method. In comparison with handcrafted method, the experimental results show that our proposed method has complexity reduction, higher precision and accurate reproducibility.

Preparation of Compositional Gradient Polymeric Films Based on Gradient Mesh Template.

In this paper, a template-filling method was found to prepare composition gradient gelatin films by incorporating α-[3-(2,3-epoxypropoxy) propyl]-ω-butyl-polydimethylsiloxane (PDMS–E) grafted gelatin (PGG) into a gradient gelatin mesh template. The method can be used to prepare other composition gradient biopolymer films. Gradient mesh template prepared by the methacrylic anhydride cross-linked gelatin under temperature gradient field. The porosity of the template decreased from 89 to 35% which was accompanied by decrease in average pore size from 160 to 50 µm. Colloidal particles about 0.9~10 µm were formed from PGG after adding them to a mixed solvent system of 9:1 (v/v) of ethanol/water, which were filled in the mesh template under vacuum (0.06 MPa). A gradient film was obtained after drying at room temperature for 48 h. The results of scanning electron microscope-energy dispersive X-ray combined with freezing microtome and Fourier transform infrared spectroscopy suggested that the distribution of the Si element along the thickness showed a typical gradient pattern, which led to hydrophilic/hydrophobic continuous changing along the thickness of film. The water vapor permeability, thermal gravimetric analysis, differential scanning calorimetry and dynamic mechanical tensile results show that the gradient films had excellent water vapor permeability and flexibility, and hence could be used as biomimetic materials and leather finishing agents.

Template-Based 3D Reconstruction of Non-rigid Deformable Object from Monocular Video

In this paper, we propose a template-based 3D surface reconstruction system of non-rigid deformable objects from monocular video sequence. Firstly, we generate a semi-dense template of the target object with structure from motion method using a subsequence video. This video can be captured by rigid moving camera orienting the static target object or by a static camera observing the rigid moving target object. Then, with the reference template mesh as input and based on the framework of classical template-based methods, we solve an energy minimization problem to get the correspondence between the template and every frame to get the time-varying mesh to present the deformation of objects. The energy terms combine photometric cost, temporal and spatial smoothness cost as well as as-rigid-as-possible cost which can enable elastic deformation. In this paper, an easy and controllable solution to generate the semi-dense template for complex objects is presented. Besides, we use an effective iterative Schur based linear solver for the energy minimization problem. The experimental evaluation presents qualitative deformation objects reconstruction results with real sequences. Compare against the results with other templates as input, the reconstructions based on our template have more accurate and detailed results for certain regions. The experimental results show that the linear solver we used performs better efficiency compared to traditional conjugate gradient based solver.

Finite element modeling of the human kidney for probabilistic occupant models: Statistical shape analysis and mesh morphing

Statistical shape analysis was conducted on 15 pairs (left and right) of human kidneys. It was shown that the left and right kidney were significantly different in size and shape. In addition, several common modes of kidney variation were identified using statistical shape analysis. Semi-automatic mesh morphing techniques have been developed to efficiently create subject specific meshes from a template mesh with a similar geometry. Subject specific meshes as well as probabilistic kidney meshes were created from a template mesh. Mesh quality remained about the same as the template mesh while only taking a fraction of the time to create the mesh from scratch or morph with manually identified landmarks. This technique can help enhance the quality of information gathered from experimental testing with subject specific meshes as well as help to more efficiently predict injury by creating models with the mean shape as well as models at the extremes for each principal component.

Nanowire-Templated Three-Dimensional out-of-Plane Fuzzy Graphene As Thin Film Supercapacitor

Supercapacitors have gained popularity as future energy storage solutions due to their simple architecture, long cycling life, pulse power supply, and high dynamic charge propagation.1 They are generally categorized as Electrical Double Layer Capacitors (EDLCs) or pseudo-capacitors.2 EDLCs store energy as electrostatic charge on the electrodes’ surfaces; their efficiency is thus limited by the electrochemically active surface area available to the electrolyte.3 Whereas, pseudo-capacitors utilize fast and reversible faradaic processes due to electro-active species localized on the electrode surface to enhance current density.1, 4 Concentration of electro-active charged species and electro-chemical efficiency governs the efficiency of these supercapacitors. Recently, carbon-based materials (such as CNTs, graphene foams, graphene aerogels) have received research interest as promising candidates for supercapacitors due to their high electrochemical surface area, high electrical conductivity and accessible surface active sites for modification with electro-active species.5 Graphene has emerged as an ideal EDLC electrode material due to its superior electrical properties and high theoretical surface area.6 Current graphene electrodes are either pinned to a two-dimensional (2D) surface (such as graphene foams) or are tethered to a 2D substrate (such as carbon nanowalls). Graphene based hybrid-nanomaterials that leverage graphene’s outstanding surface-to-volume ratio coupled with pseudo-capacitive species for high efficiency supercapacitors have not been demonstrated to date. Here we demonstrate that direct synthesis of three-dimensional (3D) out-of-plane fuzzy graphene (3DFG) on Si nanowire (SiNW) mesh template (NT-3DFG) provides an ideal surface for functionalization with electro-active species to develop EDLC and pseudo-capacitive supercapacitors. We report fine control over 3DFG flake size and edge density by varying the partial pressure of CH4 precursor, plasma enhanced chemical vapor deposition (PECVD) synthesis process time, and PECVD synthesis temperature (Figure 1.A and B).7 Through electron microscopy (SEM and TEM) and Raman spectroscopy a distinct increase in single-to-few layer out-of-plane graphene edges is observed. High density of graphene edges presents high concentration of active sites for surface functionalization through surface doping, such as that through treatment with HNO3. Post treatment, the electrical conductivity of NT-3DFG is observed to be as high as 2400 S m-1. Leveraging on graphene’s outstanding surface-to-volume ratio, we have developed a material capable of attaining electrochemically active surface area of ca. 1017 m2 g-1. The introduction of electro-active species on this high surface area material renders specific capacitance as high as 87 ± 8 F g-1 (Figure 1.C). This value is further enhanced by decorating the template with metal oxide nanoparticles. The reported novel graphene based hybrid-nanomaterial shows great potential to be utilized in next-generation energy storage solutions. Figure 1. Characterization of NT-3DFG. (A) SEM image of NT-3DFG synthesized with increasing partial pressure of CH4 and increasing PECVD process time. (B) Effect of increasing PECVD process temperature on NT-3DFG synthesized under 25 mTorr partial pressure of CH4 for 10 min. (C) Cyclic voltammetry characterization of NT-3DFG before and after HNO3 treatment. (I) Representative cyclic voltammograms presenting double layer capacitance of NT-3DFG. Blue, yellow and red denote Au working electrode, NT-3DFG synthesized under 25 mTorr partial pressure of CH4 for 30 min and NT-3DFG synthesized under 25 mTorr partial pressure of CH4 for 90 min, respectively. Dashed lines represent respective samples after 2-hour HNO3 treatment. (II) Current density as a function of scan rate. Blue, yellow and red denote Au working electrode, NT-3DFG synthesized under 25 mTorr partial pressure of CH4 for 30 min and NT-3DFG synthesized under 25 mTorr partial pressure of CH4 for 90 min, respectively. Closed and open square represent samples before and after 2-hour HNO3 treatment, respectively.

(Invited) Multiscale Topological Design of Biological Interfaces to Novel Nanocarbons

We focus on developing a new class of nanoscale materials and novel strategies for the investigation of biological entities at multiple length scales, from the molecular level to complex cellular networks. Our highly flexible bottom-up nanomaterials synthesis capabilities allow us to form unique hybrid-nanomaterials. Recently, we have demonstrated highly controlled synthesis of 3D out-of-plane single- to few-layer fuzzy graphene (3DFG) on a Si nanowire (SiNW) mesh template. By varying graphene growth conditions, we control the size, density, and electrical properties of the NW templated 3DFG (NT-3DFG). This flexible synthesis inspires formation of complex hybrid-nanomaterials with tailored optical and electrical properties to be used in future applications such as biosensing, and bioelectronics. Currently, we target the limits of cell-nanodevices interfaces using nanosensor based array assembled in 3D with subcellular spatial resolution (<5μm) and μsec temporal resolution. Our approach enables simultaneous multiplexed electrical measurements to directly monitor the development of electrical activities of microscale tissues (μtissues, ca. 100-400μm) which are engineered from induced pluripotent stem cell or embryonic stem cell derived cardiomyocytes. Last, we have developed a unique transparent graphene-based electrical platform that enables concurrent electrical and optical investigation of ES-derived cardiomyocytes’ intracellular processes and intercellular communication. In summary, the exceptional synthetic control and flexible assembly of nanomaterials provide powerful tools for fundamental studies and applications in life science, and open up the potential to seamlessly merge either nanomaterials-based platforms or unique nanosensor geometries and topologies with cells, fusing nonliving and living systems together.

Nanowire-Templated Three-Dimensional Out-of-Plane Fuzzy Graphene as an Oxygen Reduction Reaction Catalyst

Rate-limiting oxygen reduction reactions (ORR) and high-cost platinum at fuel cell cathodes are substantial barriers to commercial fuel cell viability. Carbon-based, metal-free ORR catalysts have high catalytic stability and can potentially dramatically reduce cost and increase efficiency of fuel cells. For increased ORR efficiency, nitrogen doping of graphene sp2-hybridized carbon lattice is utilized, to induce a net positive charge on adjacent C atoms to alter the O2 chemisorption mode and attract electrons from the ­electrode. We have recently reported synthesis of a novel graphene-based hybrid-nanomaterial composed of three-dimensional (3D) out-of-plane fuzzy graphene (3DFG) on 3D Si nanowire mesh template (NT-3DFG). Leveraging graphene’s outstanding surface-to-volume ratio and electrical conductivity, we attained exceptional electrochemically active surface area of ca. 1017 m2 g-1 (with high density of exposed, active graphene edges) and electrical conductivity of ca. 2400 S m-1. Here we report fine control over 3DFG flake size and edge density by varying the partial pressure of CH4 precursor as well as the plasma enhanced chemical vapor deposition (PECVD) process time and temperature (Figure 1.A-B). XPS analysis of C1s confirms the presence of graphite via the sp2 hybridized C bonds in 3DFG structures (Figure 1.C.I and III). We also show both in-situ and post synthesis N-doping of NT-3DFG through either incorporation of N2 during the PECVD process or post-synthesis N2-plasma treatment. XPS analysis of N1s confirms the presence of pyridinic-, pyrrolic-, and graphitic-N doping in the NT-3DFG structure (Figure 1.C.II and IV). In-situ N-doping of NT-3DFG resulted in ca. 87% pyridinic-N doping compared to ca. 52% through post-synthesis N2-plasma treatment. This pyridinic-N stabilizes the active site responsible for the chemical disproportionation of peroxide ions during ORR. Through cyclic voltammetry under acidic conditions, we demonstrate the functionality and properties of N-doped NT-3DFG as an ORR catalyst. With pyridinic-N doping and a high density of graphene edges, N-doped NT-3DFG demonstrates greater ORR efficiency than existing graphene-based hybrid nanomaterials. Figure 1. Characterization of N-doped NT3DFG. (A) SEM image of NT-3DFG synthesized with increasing partial pressure of CH4 and increasing PECVD process time. (B) Effect of increasing PECVD process temperature on NT-3DFG synthesized under 25 mTorr partial pressure of CH4 for 10 min. (C) X-ray photoelectron (XPS) spectra of (I) C1s and (II) N1s of in-situ N-doped NT-3DFG synthesized under 25 mTorr partial pressure of CH4 and 400 mTorr partial pressure of N2 for 30 min at 800˚C; and (III) C1s and (IV) N1s of NT-3DFG synthesized under 25 mTorr partial pressure of CH4 for 30 min at 800˚C doped with N post-synthesis under 300 mTorr partial pressure of N2 for 5 min at 300˚C. Cyan, purple, pink, red, green and blue represent C sp2, C sp3, C=O, Pyridinic N, Pyrrolic N and Graphitic N XPS spectra, respectively. Figure 1

SiSSR: Simultaneous subdivision surface registration for the quantification of cardiac function from computed tomography in canines.

Recent improvements in cardiac computed tomography (CCT) allow for whole-heart functional studies to be acquired at low radiation dose (<2mSv) and high-temporal resolution (<100ms) in a single heart beat. Although the extraction of regional functional information from these images is of great clinical interest, there is a paucity of research into the quantification of regional function from CCT, contrasting with the large body of work in echocardiography and cardiac MR. Here we present the Simultaneous Subdivision Surface Registration (SiSSR) method: a fast, semi-automated image analysis pipeline for quantifying regional function from contrast-enhanced CCT. For each of thirteen adult male canines, we construct an anatomical reference mesh representing the left ventricular (LV) endocardium, obviating the need for a template mesh to be manually sculpted and initialized. We treat this generated mesh as a Loop subdivision surface, and adapt a technique previously described in the context of 3-D echocardiography to register these surfaces to the endocardium efficiently across all cardiac frames simultaneously. Although previous work performs the registration at a single resolution, we observe that subdivision surfaces naturally suggest a multiresolution approach, leading to faster convergence and avoiding local minima. We additionally make two notable changes to the cost function of the optimization, explicitly encouraging plausible biological motion and high mesh quality. Finally, we calculate an accepted functional metric for CCT from the registered surfaces, and compare our results to an alternate state-of-the-art CCT method.

All cellulose electrospun water purification membranes nanotextured using cellulose nanocrystals

Cellulose acetate (CA) fibers were electrospun on a mesh template to create specific surface and pore structures for membrane applications. The mesh template CA fiber mats were impregnated with cellulose nanocrystals at varying weight percentages. The membranes showed nanotextured surfaces and improved mechanical properties post impregnation. More importantly, the hydrophilicity of the original CA fibers was increased from a hydrophobic contact angle of 102°–0° thereby creating an anti-fouling membrane surface structure. The membranes showed rejection of 20–56% for particles of 0.5–2.0 μm, indicating potential of these membranes in rejecting microorganisms from water. Furthermore, high rejection of dyes (80–99%) by adsorption and potential application as highly functional affinity membranes was demonstrated. These membranes can therefore be utilized as all-cellulose, green, scalable and low cost high flux membranes (> 20,000 LMH) for water cleaning applications in food industry where microorganisms and charged contaminants are to be removed.

Learning a model of facial shape and expression from 4D scans

The field of 3D face modeling has a large gap between high-end and low-end methods. At the high end, the best facial animation is indistinguishable from real humans, but this comes at the cost of extensive manual labor. At the low end, face capture from consumer depth sensors relies on 3D face models that are not expressive enough to capture the variability in natural facial shape and expression. We seek a middle ground by learning a facial model from thousands of accurately aligned 3D scans. Our FLAME model (Faces Learned with an Articulated Model and Expressions) is designed to work with existing graphics software and be easy to fit to data. FLAME uses a linear shape space trained from 3800 scans of human heads. FLAME combines this linear shape space with an articulated jaw, neck, and eyeballs, pose-dependent corrective blendshapes, and additional global expression blendshapes. The pose and expression dependent articulations are learned from 4D face sequences in the D3DFACS dataset along with additional 4D sequences. We accurately register a template mesh to the scan sequences and make the D3DFACS registrations available for research purposes. In total the model is trained from over 33, 000 scans. FLAME is low-dimensional but more expressive than the FaceWarehouse model and the Basel Face Model. We compare FLAME to these models by fitting them to static 3D scans and 4D sequences using the same optimization method. FLAME is significantly more accurate and is available for research purposes (http://flame.is.tue.mpg.de).

Numerical simulation of holes and inclusions using adaptive polygonal finite element method

An adaptive polygonal finite element method using the techniques of cut-cell and quadtree refinement is presented for modeling holes and inclusions in 2-D solids. A mesh template is used to ensure the high-quality refined elements generated in quadtree refinement. By coupling the level set method, the polygonal computational mesh is directly extracted from the mesh template in every adaptive cycle. An error estimator based on recovery stress is devoted for adaptive purpose, which allows the mesh where it is needed is further refining. This method allows to model arbitrary shape holes and inclusions in arbitrary-geometry 2-D solid using the initial mesh of few rectangular elements, which considerably simplifies construction of the finite element model. And one curved boundary can be accurately represented though several steps of refinement. Numerical examples are solved and the obtained results are compared with reference solutions to show the simplicity and efficiency of the proposed method.

Human Head Stiffness Rendering

Human head stiffness rendering is important in haptic interactive applications, because it defines a realistic physical interaction between human operator(s) and a human avatar created in a virtual environment. In this paper, we propose a hybrid method for rendering the appropriate stiffness property on a human head polygon mesh that combines popular haptic rendering approaches: study the sophisticated deformation behavior of a deformable object and then interpret and render this behavior as the resulting stiffness property on the individual’s head mesh. The stiffness property is estimated from a registered and shape-adapted skull template mesh as a reference and modeled from the deformation behavior of soft tissue in a finite-element method (FEM) framework. Our method consists of different procedures, including facial landmark detection, model registration using the iterative closest point technique, adaptive shape modification processed with a modified weighted free-form deformation, and FEM simulation. After the stiffness property is rendered on a head polygon mesh, we perform a user study by inviting participants to experience the haptic feedback rendered from our results. According to the participants’ feedback, the stiffness property of the head polygon mesh is properly rendered, because it satisfies their expectations.

SURFACE-BASED ANALYSIS OF SUB-CORTICAL STRUCTURES IN TAU AND AMYLOID PET IMAGING: AN ALZHEIMER'S DISEASE STUDY

The extracellular amyloid plaques and neurofibrillary tangles are important hallmarks of Alzheimer disease (AD) spectrum. The recent development of positron emission tomography (PET) tracers has enabled human to detect neuritic plaques or neurofibrillary tangles in vivo. In this study, we recruited cognitive normal (CN) subjects (6 normal control and 27 subjective memory impairment subjects), 54 mild cognitive impairment (MCI) patients, 26 AD patients with T1-weighted brain magnetic resonance imaging (MRI), amyloid PET and tau PET. We constructed subcortical surface meshes and registered to the template mesh in order to provide vertex correspondences. Each vertices of subcortical surface acquired standardized uptake value ratios (SUVR) normalized by mean uptake of cerebellar cortex from PET images which were registered to the T1-weighted MRI images. We performed group comparison between three groups using permutation test and false discovery rate (FDR) correction. In the amyloid PET study, AD patients showed significant increased SUVR in the bilateral caudate nucleus, the bilateral putamen, the left globus pallidus, the right amygdala compared with CN subjects. Also SUVR in these subcortical regions and the right globus pallidus were higher in the MCI patients than CN subjects. Whereas SUVR of the bilateral hippocampus was higher in the CN subjects than AD patients. MCI patients had higher SUVR in the left hippocampus than AD patients. In the tau PET study, AD patients exhibited greater SUVR in the bilateral amygdala, the left hippocampus and the left putamen relative to CN subjects. Except for the left putamen, MCI patients had greater SUVR in the same regions relative to CN subjects. Contrary to the amyloid PET study, AD patients had greater SUVR in the left hippocampus than MCI patients.

Preparation, characterization, and application of TiO2-patterned polyimide film as a photocatalyst for oxidation of organic contaminants

Photocatalytically active TiO2-patterned polyimide (PI) films (PI-TiO2) were fabricated using thermal transfer patterning (TTP). When subjected to hot pressing, the TiO2 nanoparticles electrosprayed on steel mesh templates were successfully transferred and formed checker plate patterns on PI film. FE-SEM studies confirmed that pressing at 350°C and 100MPa was optimum for obtaining patterns with uniform TiO2 coverage. When the quantity of TiO2 on the template increased, the amount of it immobilized on PI film also increased from 0.3245 to 1.2378mg per 25cm2. XPS studies confirmed the presence TiO2 on the patterns, and indicated the formation of carboxylic acid and amide groups on the PI surface during TTP. When tested under UVA irradiation, PI-TiO2 with 1.2378mg/25cm2 TiO2 loading exhibited the highest photocatalytic performance for methylene blue (10μM) degradation, with a rate constant of 0.0225min−1 and stable photocatalytic efficacy for 25 cycles of reuse. The PI-TiO2 was also successfully used to degrade amoxicillin, atrazine, and 4-chlorophenol. During photocatalysis, the toxicity of 4-chlorophenol against Vibrio fischeri and the antibiotic activity of amoxicillin against Escherichia coli were decreased. Overall, TTP was found to be a potentially scalable method for fabricating robust immobilized TiO2 photocatalyst.

Nanowire-Mesh-Templated Growth of Out-of-Plane Three-Dimensional Fuzzy Graphene.

Graphene, a honeycomb sp2 hybridized carbon lattice, is a promising building block for hybrid-nanomaterials due to its electrical, mechanical, and optical properties. Graphene can be readily obtained through mechanical exfoliation, solution-based deposition of reduced graphene oxide (rGO), and chemical vapor deposition (CVD). The resulting graphene films' topology is two-dimensional (2D) surface. Recently, synthesis of three-dimensional (3D) graphitic networks supported or templated by nanoparticles, foams, and hydrogels was reported. However, the resulting graphene films lay flat on the surface, exposing 2D surface topology. Out-of-plane grown carbon nanostructures, such as vertically aligned graphene sheets (VAGS) and vertical carbon nanowalls (CNWs), are still tethered to 2D surface. 3D morphology of out-of-plane growth of graphene hybrid-nanomaterials which leverages graphene's outstanding surface-to-volume ratio has not been achieved to date. Here we demonstrate highly controlled synthesis of 3D out-of-plane single- to few-layer fuzzy graphene (3DFG) on a Si nanowire (SiNW) mesh template. By varying graphene growth conditions (CH4 partial pressure and process time), we control the size, density, and electrical properties of the NW templated 3DFG (NT-3DFG). 3DFG growth can be described by a diffusion-limited-aggregation (DLA) model. The porous NT-3DFG meshes exhibited high electrical conductivity of ca. 2350 S m-1. NT-3DFG demonstrated exceptional electrochemical functionality, with calculated specific electrochemical surface area as high as ca. 1017 m2 g-1 for a ca. 7 μm thick mesh. This flexible synthesis will inspire formation of complex hybrid-nanomaterials with tailored optical and electrical properties to be used in future applications such as sensing, and energy conversion and storage.

DeepGarment : 3D Garment Shape Estimation from a Single Image

3D garment capture is an important component for various applications such as free-view point video, virtual avatars, online shopping, and virtual cloth fitting. Due to the complexity of the deformations, capturing 3D garment shapes requires controlled and specialized setups. A viable alternative is image-based garment capture. Capturing 3D garment shapes from a single image, however, is a challenging problem and the current solutions come with assumptions on the lighting, camera calibration, complexity of human or mannequin poses considered, and more importantly a stable physical state for the garment and the underlying human body. In addition, most of the works require manual interaction and exhibit high run-times. We propose a new technique that overcomes these limitations, making garment shape estimation from an image a practical approach for dynamic garment capture. Starting from synthetic garment shape data generated through physically based simulations from various human bodies in complex poses obtained through Mocap sequences, and rendered under varying camera positions and lighting conditions, our novel method learns a mapping from rendered garment images to the underlying 3D garment model. This is achieved by training Convolutional Neural Networks CNN-s to estimate 3D vertex displacements from a template mesh with a specialized loss function. We illustrate that this technique is able to recover the global shape of dynamic 3D garments from a single image under varying factors such as challenging human poses, self occlusions, various camera poses and lighting conditions, at interactive rates. Improvement is shown if more than one view is integrated. Additionally, we show applications of our method to videos.

Nanowire Templated Growth of Three-Dimensional Fuzzy Graphene

Graphene, a two-dimensional (2D) hexagonal arrangement of sp2 carbon, is gaining popularity as a material for electrochemical sensors. Graphene outstanding electrical properties has led researchers to develop three-dimensional (3D) atomic layer graphene materials with increased surface area as more efficient electrodes. Although 3D graphene materials such as foams and multilayered carbon nanowalls have already been synthesized, synthesis of 3D vertical atomic layer graphene still remains a challenge. Here we demonstrate a novel synthesis of high density single to few layer vertical graphene on semiconductor nanowire mesh templates. The presence of graphene on the nanowires was confirmed by Raman spectroscopy. The progression of the templated growth of the 3D graphene flakes was verified by using scanning electron microscopy. Moreover, the growth of single to few layer crystalline graphene flakes that are vertically orientated with respect to the nanowire axis was validated by transmission electron microscopy. The sheet resistance of the new hybrid nanomaterial decreased with an increase in graphene flake size and density. Lastly, high electrochemically active surface area of the material was ascertained by cyclic voltammetry. These results pave way for the use of 3D vertical atomic layer graphene on nanowire mesh templates as electrodes for electrochemical sensing of biomolecules, quantification of fast-electron transfer reactions, and energy harvesting in fuel cells.

Multilevel active registration for kinect human body scans: from low quality to high quality

Registration of 3D human body has been a challenging research topic for over decades. Most of the traditional human body registration methods require manual assistance, or other auxiliary information such as texture and markers. The majority of these methods are tailored for high-quality scans from expensive scanners. Following the introduction of the low-quality scans from cost-effective devices such as Kinect, the 3D data capturing of human body becomes more convenient and easier. However, due to the inevitable holes, noises and outliers in the low-quality scan, the registration of human body becomes even more challenging. To address this problem, we propose a fully automatic active registration method which deforms a high-resolution template mesh to match the low-quality human body scans. Our registration method operates on two levels of statistical shape models: (1) the first level is a holistic body shape model that defines the basic figure of human; (2) the second level includes a set of shape models for every body part, aiming at capturing more body details. Our fitting procedure follows a coarse-to-fine approach that is robust and efficient. Experiments show that our method is comparable with the state-of-the-art methods for high-quality meshes in terms of accuracy and it outperforms them in the case of low-quality scans where noises, holes and obscure parts are prevalent.