3D Texture Research Articles

Filtering After Shading With Stochastic Texture Filtering

2D texture maps and 3D voxel arrays are widely used to add rich detail to the surfaces and volumes of rendered scenes, and filtered texture lookups are integral to producing high-quality imagery. We show that applying the texture filter after evaluating shading generally gives more accurate imagery than filtering textures before BSDF evaluation, as is current practice. These benefits are not merely theoretical, but are apparent in common cases. We demonstrate that practical and efficient filtering after shading is possible through the use of stochastic sampling of texture filters. Stochastic texture filtering offers additional benefits, including efficient implementation of high-quality texture filters and efficient filtering of textures stored in compressed and sparse data structures, including neural representations. We demonstrate applications in both real-time and offline rendering and show that the additional error from stochastic filtering is minimal. We find that this error is handled well by either spatiotemporal denoising or moderate pixel sampling rates.

A step towards 6D WAXD tensor tomography.

X-ray scattering/diffraction tensor tomography techniques are promising methods to acquire the 3D texture information of heterogeneous biological tissues at micrometre resolution. However, the methods suffer from a long overall acquisition time due to multi-dimensional scanning across real and reciprocal space. Here, a new approach is introduced to obtain 3D reciprocal information of each illuminated scanning volume using mathematic modeling, which is equivalent to a physical scanning procedure for collecting the full reciprocal information required for voxel reconstruction. The virtual reciprocal scanning scheme was validated by a simulated 6D wide-angle X-ray diffraction tomography experiment. The theoretical validation of the method represents an important technological advancement for 6D diffraction tensor tomography and a crucial step towards pervasive applications in the characterization of heterogeneous materials.

Unveiling Texture and Topography of Fatty Acid Langmuir Films: Domain Stability and Isotherm Analysis.

3D texturing by self-assembly at the air-water interface has recently been proposed. The hypothesis of this work is that, if this is true, such domain formation should be inferable directly from pressure-area isotherms and be thermodynamically stable. Monolayers of branched fatty acid mixtures with straight chain analogues and their stability are thus studied using a combination of pressure-area isotherms, thermodynamic analysis, in situ Brewster angle microscopy, and atomic force microscopy of both LB-deposited and drop-cast films on silicon wafers. Isotherms reflecting the behavior of monodisperse 3D domains are shown to be independent of compression rate and display long-term stability. Gibbs analysis further confirms the thermodynamic rather than kinetic origin of such novel species by revealing that deviations from ideal mixing can be explained only a priori by differences in the topography of the water surface, thus also indirectly confirming the self-assembly deformation of the water interface. The intrinsic self-assembly curvature and miscibility of the two fatty acids is confirmed by drop-casting, which also provides a rapid, tunable thin-film preparation approach. Finally, the longevity of the nanostructured films is extraordinary, the long-range order of the deposited films increases with equilibration time at the water interface, and the integrity of the nanopatterns remains intact on the scale of years.

Postprocessing Workflow for Laboratory Diffraction Contrast Tomography: A Case Study on Chromite Geomaterials.

Texture stands as a fundamental descriptor in the realms of geology and earth and planetary science. Beyond offering insights into the geological processes underlying mineral formation, its characterization plays a pivotal role in advancing engineering applications, notably in mining, mineral processing, and metal extraction, by providing quantitative data for predictive modeling. Laboratory diffraction contrast tomography (LabDCT), a recently developed 3D characterization technique, offers nondestructive measurement of grain phases including their morphology, distribution, and crystal orientation. It has recently shown its potential to assess 3D textures in complex natural rock samples. This study looks at improving on previous work by examining the artifacts and presents a novel postprocessing workflow designed to correct them. The workflow is developed to rectify inaccurate grain boundaries and interpolate partially reconstructed grains to provide more accurate results and is illustrated using multi-scan examples on chromite sands and natural chromitite from the Upper Group 2 Reef layer in South Africa. The postcorrected LabDCT results were validated through qualitative and quantitative assessment using 2D electron back-scattered diffraction on polished sample surfaces. The successful implementation of this postprocessing workflow underscores its substantial potential in achieving precise textural characterization and will provide valuable insights for both earth science and engineering applications.

All-Printed Finger-Inspired Tactile Sensor Array for Microscale Texture Detection and 3D Reconstruction.

Electronic skins are expected to replicate a human-like tactile sense, which significantly detects surface information, including geometry, material, and temperature. Although most texture features can be sensed in the horizontal direction, the lack of effective approaches for detecting vertical properties limits the development of artificial skin based on tactile sensors. In this study, an all-printed finger-inspired tactile sensor array is developed to realize the 3D detection and reconstruction of microscale structures. A beam structure with a suspended multilayer membrane is proposed, and a tactile sensor array of 12 units arranged in a dual-column layout is developed. This architecture enables the tactile sensor array to obtain comprehensive geometric information of micro-textures, including 3D morphology and clearance characteristics, and optimizes the 3D reconstruction patterns by self-calibration. Moreover, an innovative screen-printing technology incorporating multilayer printing and sacrificial-layer techniques is adopted to print the entire device. In additon, a Braille recognition system utilizing this tactile sensor array is developed to interpret Shakespeare's quotes printed in Grade 2 Braille. The abovementioned demonstrations reveal an attractive future vision for endowing bioinspired robots with the unique capability of touching and feeling the microscale real world and reconstructing it in the cyber world.

Effect of 2-Mercapto-1-methylimidazole on the Electrodeposition of Nickel on an Ordered Au(111) Electrode.

A nickel film electroplated onto a metal substrate can be used as a catalyst for water splitting and a magnetic material for spin valves. Although the nucleation and growth of Ni on Au(111) have already been examined with in situ scanning tunneling microscopy (STM), the current study provides new insights of the structure of the first layer of Ni on an ordered Au(111) electrode in 0.1 M KSO4 + 1 mM H2SO4 + 10 mM NiSO4 (pH 3). Prolonged STM scanning of the Ni monolayer on a Au(111) electrode revealed interfacial mixing to produce a surface alloy, initially assuming segregated Ni domains and later transforming them to a homogeneous Ni/Au phase. The formation of the Ni/Au(111) surface alloy affected the structure of the subsequent bulk Ni deposition. The inclusion of 2-mercapto-1-methylimidazole (MMI) in the deposition bath incurred Ni deposition at a less negative potential and a faster rate, resulting in an overall 5.3 times more Ni deposited on the Au electrode in potentiodynamic experiments. MMI molecules were adsorbed on the Ni deposit to prevent Ni dissolution in the Au(111) electrode. MMI could catalyze the presumed rate-determining step from Ni2+ to Ni+ en route to the metallic Ni. The resultant Ni film with MMI had a 3D texture without a preferred crystal orientation on the Au electrode, as opposed to a layer type growth of Ni on Au(111) without MMI.

Computed Tomography of Scheelite Ore, Kara, Australia: Morphological Characterisation and Modal Mineralogy

Metal ores are mineralogically characterised to understand their genesis in order to allow informed decisions on mineral processing and to recognise likely environmental risks upon mining. However, standard mineralogical techniques generate only two-dimensional information at best, which in addition may be subject to sampling and stereological errors. By contrast, computed tomography (CT) is a non-destructive imaging technique that allows three-dimensional analysis of solid materials. In the present study, two ore types of the Kara Fe-W deposit (Australia) were characterised using CT to examine their mineral texture and modal mineralogy as well as scheelite distribution and ore grade (WO3). The results show that scheelite is primarily associated with hydrous phases (e.g., epidote, chlorite, amphibole) and occurs as massive or disseminated mineral as well as vein-fill at minor and trace concentrations. This study demonstrates that CT of scheelite ore enables accurate 3D texture visualisation (volume, grain size distribution) and yields valid quantitative data on modal mineralogy and WO3 grade of individual ore samples. Consequently, CT analysis of scheelite-bearing ore provides information relevant for ore genesis studies and comminution strategies for the possible recovery of scheelite as a by-product from metalliferous ores.

Remote sensing‐based mapping of structural building damage in the Ahr valley

AbstractFlood damage data are needed for various applications. Structural damage of buildings can reflect not only the economic damage but also the life‐threatening condition of a building, which provide crucial information for disaster response and recovery. Since traditional on‐site data collection shortly after a disaster is challenging, remote sensing data can be of great help, cover a wider area and be deployed earlier in time than on‐site surveys. However, this has its challenges and limitations. We elucidate on that by presenting two case studies from flash floods in Germany. First, we assessed the reliability of an existing flood damage schema, which differentiates from minor (structural) damage to complete building collapse. We compared two on‐site raters of the 2016 Braunsbach flood, reaching an excellent level of reliability. Second, we mapped structural building damage after the flood in the Ahr valley in 2021 using a textured 3D mesh and orthophotos. Here, we evaluated the remote sense‐based damage mapping done by three raters. Although the heterogeneity of ratings using remote sensing data is larger than among on‐site ratings, we consider it fit‐for‐purpose when compared with on‐site mapping, especially for event documentation and as basis for financial damage estimation and less complex numerical modelling.

Diverse and Stable 2D Diffusion Guided Text to 3D Generation with Noise Recalibration

In recent years, following the success of text guided image generation, text guided 3D generation has gained increasing attention among researchers. Dreamfusion is a notable approach that enhances generation quality by utilizing 2D text guided diffusion models and introducing SDS loss, a technique for distilling 2D diffusion model information to train 3D models. However, the SDS loss has two major limitations that hinder its effectiveness. Firstly, when given a text prompt, the SDS loss struggles to produce diverse content. Secondly, during training, SDS loss may cause the generated content to overfit and collapse, limiting the model's ability to learn intricate texture details. To overcome these challenges, we propose a novel approach called Noise Recalibration algorithm. By incorporating this technique, we can generate 3D content with significantly greater diversity and stunning details. Our approach offers a promising solution to the limitations of SDS loss.

HABERTAN: Game Petualangan 3D Dengan Tema Pemilahan Sampah Sebagai Upaya Pendekatan Inovatif Untuk Pengenalan Lingkungan

The increasing awareness of the importance of maintaining forest cleanliness as a primary ecosystem is becoming more urgent, especially in remote areas with limited deep socialization. This research aims to develop an innovative game titled "HABERTAN" focusing on waste sorting in forest areas to raise public awareness of the waste present in the forest. By utilizing a 3D model for visual assets with stages of 2D sketch, 3D modeling, UV Mapping, and Texture Baking. The development of this game is conducted using the Analysis, Design, Development, Implementation, and Evaluation (ADDIE) method. The ADDIE method is used to ensure a systematic game development process, starting from needs analysis to performance evaluation. The goal of this game is to provide players with an interactive experience that not only entertains but also provides a deep understanding of the impact of waste on forest sustainability. The game "HABERTAN (Let's Clean the Forest)" is designed to provide players with a fun and educational learning experience. The results of the development of this game show that "HABERTAN" provides a unique experience for players, with the ability to learn while playing. It is hoped that this game can be an effective tool in raising public awareness of the importance of maintaining forest cleanliness, especially in the context of waste sorting. Through this innovative approach, it is hoped to encourage active participation from the community in preserving forests as extremely valuable natural resources.

Lightweight and high-strength textured fibrous Si3N4 3D scaffold seeded with β-Si3N4 particles prepared via freeze casting

Highly porous Si3N4 ceramics with unidirectionally aligned pore channels are gaining significant attention across various fields due to their outstanding functional capabilities. However, achieving high strength in such unidirectional highly porous Si3N4 ceramics remains challenging. Herein, we design and fabricate a novel β-Si3N4 scaffold composed of directionally aligned lamellar walls with a textured microstructure by directionally freeze casting of α-Si3N4 suspensions with fine elongated β-Si3N4 seeds addition, followed by liquid phase sintering. During the sintering, the scaffold exhibited anisotropic shrinkage, and fibrous β-Si3N4 grains were synthesized through epitaxial growth on the seeds preferentially oriented or the nuclei originated from α-Si3N4 powders, resulting in the grains aligned parallel to lamellar walls and bridged the walls. Seed additions of 7 to 15 wt% were beneficial for the optimized distribution of the two types of β-Si3N4 grains, which contributed to the excellent resistance to bucking-induced fracture for the walls. Compared with other unidirectional porous Si3N4 prepared by freeze-casting in the literature, the Si3N4 scaffold exhibited outstanding compressive strength, ranging from 2.8 to 22.0 MPa, as the porosity decreased from 94.4 % to 88.0 % and the density increased from 175 to 365 mg/cm3. The lightweight and strong Si3N4 scaffolds are promising candidates for engineering applications in harsh environments.

FLATTENING COMPLEX ARCHITECTURAL SURFACES: PHOTOGRAMMETRIC 3D MODELS CONVERTED INTO 2D MAPS

Abstract. The paper describes a workflow to flatten 3D photogrammetric models of undevelopable surfaces into unfragmented 2D texture maps. The aim is to create a texture map with reduced fragmentation compared to typical photogrammetric texture files associated with 3D models. Geometric reformatting of the mesh is required to achieve an unfragmented final texture image with enough visual quality to allow for its use in 2D editing software (e.g., Photoshop, Illustrator, etc.). With a lighter model and defragmented texture, graphic documentation of conditions, treatments, or other relevant information can be performed directly. The approach considers both simple and complex architectural surfaces, with particular attention to elements that cannot be developed without introducing distortions. In the case of historic buildings, such surfaces constitute the majority, especially in the case of decorative elements and irregular vaulted systems. The approach extends to full 3D models, particularly those where orthomosaics would result in stretched details. We will discuss two methods: the first is particularly suitable when the photogrammetric project (oriented images) is still available, and the second applies to generic 3D models without the availability of the original images.

Simulation and analysis of micro-textured rough curved surface based on fractal characterization method

PurposeMicro-texture is processed on the surface to reduce the friction of the contact surface, and its application is more and more extensive. The purpose of this paper is to create a texture function model to study the influence of surface parameters on the accuracy of the simulated surface so that it can more accurately reflect the characteristics of the real micro-textured surface.Design/methodology/approachThe microstructure function model of rough surfaces is established based on fractal geometry and polar coordinate theory. The offset angle θ is introduced into the fractal geometry function to make the surface asperity normal perpendicular to the tangent of the surface. The 2D and 3D contour surfaces of the surface groove texture are analyzed by MATLAB simulation. The effects of fractal parameters (D and G) and texture parameter h on the curvature of the surface micro-texture model were studied.FindingsThis paper more accurately characterizes the textured 3D curved surface, especially the surface curvature. The scale coefficient G significantly affects curvature, and the influence of fractal dimension D and texture parameters on curvature can be ignored.Originality/valueThe micro-texture model of the rough surface was successfully established, and the range of fractal parameters was determined. It provides a new method for the study of surface micro-texture tribology.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-09-2023-0298/

Modeling and analysis for material removal and surface roughness in fluid jet polishing of optical glass

AbstractFluid jet polishing (FJP) is a non-contact polishing technology that can fabricate free-form optical surfaces with sub-micron-level form accuracy and nano-level surface roughness, especially for hard and brittle materials. The surface generation model of FJP can be used to guide the determination and optimization of process parameters and is of great significance for understanding the evolution mechanism of surface microtopography. However, predictive models for the microscopic topography of polished surfaces are still lacking. This study established a macroscopic surface profile model for predicting 3D material removal characteristics and surface texture by combining the 3D computer fluid dynamics (CFD) simulation model and single-particle erosion mechanism. A fractal theory-based erosion model has been built to calculate the material removal caused by the erosion of a single abrasive particle on the rough surface; thus, it predicts the micro-topography and surface roughness of the polished samples. A series of polishing experiments were conducted to analyze the feasibility and accuracy of the model quantitatively and study the influence mechanism of process parameters on the material removal characteristics and surface quality. Results indicated that the models could well predict material removal and surface roughness. The prediction accuracy of the surface roughness Ra and maximum removal depth is better than 91.6% and 90%, respectively. It is also found that the material removal rate of FJP could reach 0.517 mm3/min, and the surface roughness convergence rate could reach 62.9%.

3D Texture Segmentation using Supervised Methods

Supervised learning methods have been widely used for image classification in various fields, including medical and industrial sectors. Some of these methods are traditional and possess certain limitations when addressing complex problems. The most common and effective approaches involve Convolutional Neural Networks (CNNs), such as U-Net. However, most studies employ CNNs in their 2D structures, which can impose limitations in classifying 3D objects. The purpose of this paper is to propose the utilization of 3D CNNs to potentially enhance the classification of 3D data, particularly X-ray micro-computed tomography images of reservoir rock samples. Our focus is on examining the performance of the 3D U-Net architecture, a supervised classification approach, in segmenting various 3D rock textures.

Progressive Learning of 3D Reconstruction Network From 2D GAN Data.

This paper presents a method to reconstruct high-quality textured 3D models from single images. Current methods rely on datasets with expensive annotations; multi-view images and their camera parameters. Our method relies on GAN generated multi-view image datasets which have a negligible annotation cost. However, they are not strictly multi-view consistent and sometimes GANs output distorted images. This results in degraded reconstruction qualities. In this work, to overcome these limitations of generated datasets, we have two main contributions which lead us to achieve state-of-the-art results on challenging objects: 1) A robust multi-stage learning scheme that gradually relies more on the models own predictions when calculating losses and 2) A novel adversarial learning pipeline with online pseudo-ground truth generations to achieve fine details. Our work provides a bridge from 2D supervisions of GAN models to 3D reconstruction models and removes the expensive annotation efforts. We show significant improvements over previous methods whether they were trained on GAN generated multi-view images or on real images with expensive annotations.

The Utilization of Virtual Reality Technology in the Scientific and Technological Protection and Cultural Inheritance of Clarke Porcelain--Taking Clarke Porcelain in the Collection of the City University of Macau as an Example

Abstract Virtual Reality (VR) technology heralds a transformative era for the safeguarding and disseminating cultural heritage. This paper examines its application through the lens of the Clark Porcelain collection at the City University of Macau, highlighting VR’s pivotal role in the scientific preservation and cultural transmission of these artifacts. By delving into the ornamental intricacies of Clark Porcelain, we evaluate VR’s effectiveness in protecting and showcasing these treasures. The study employs advanced techniques, including 3D virtual scene modeling, texture mapping, and collision detection, to replicate a museum setting, thus elevating the user’s interactive experience. An audience satisfaction survey indicates positive feedback, with relaxation and aesthetic satisfaction scores averaging 4.65 and 4.53, respectively. Moreover, ANOVA results reveal significant technological acceptance disparities across age groups. The Analysis further underscores VR’s substantial impact on cultural heritage promotion, noting the potential for better integration of Clark Porcelain with contemporary technologies. Virtual reality emerges as a formidable tool in the scientific conservation and cultural legacy of Clark Porcelain, offering fresh insights and technical backing for the modernization of traditional cultural heritage preservation.

Unveiling the crystal and magnetic texture of iron oxide nanoflowers.

Iron oxide nanoflowers (IONF) are densely packed multi-core aggregates known for their high saturation magnetization and initial susceptibility, as well as low remanence and coercive field. This study reports on how the local magnetic texture originating at the crystalline correlations among the cores determines the special magnetic properties of individual IONF over a wide size range from 40 to 400 nm. Regardless of this significant size variation in the aggregates, all samples exhibit a consistent crystalline correlation that extends well beyond the IONF cores. Furthermore, a nearly zero remnant magnetization, together with the presence of a persistently blocked state, and almost temperature-independent field-cooled magnetization, support the existence of a 3D magnetic texture throughout the IONF. This is confirmed by magnetic transmission X-ray microscopy images of tens of individual IONF, showing, in all cases, a nearly demagnetized state caused by the vorticity of the magnetic texture. Micromagnetic simulations agree well with these experimental findings, showing that the interplay between the inter-core direct exchange coupling and the demagnetizing field is responsible for the highly vortex-like spin configuration that stabilizes at low magnetic fields and appears to have partial topological protection. Overall, this comprehensive study provides valuable insights into the impact of crystalline texture on the magnetic properties of IONF over a wide size range, offering a deeper understanding of their potential applications in fields such as biomedicine and water remediation.

Topological transformation of magnetic hopfion in confined geometries

Three-dimensional (3D) topological magnetic structures have attracted enormous interest due to their exceptional spatial structures and intriguing physics. Hopfions, characterized by the Hopf index, are 3D spin textures that emerged as closed twisted skyrmion strings. A comprehensive understanding of magnetic structural transitions within nanostructures is crucial for their applications in spintronics devices. Despite the demonstration of stabilization and current-driven dynamics of hopfion, their behavior in geometric confinement has remained unexplored. Here, we investigate the transformation between hopfions and torons in various nanostructures using micromagnetic simulations. By tailoring the axial ratio of elliptical nanodisks, the elliptical hopfion is found to be transformed into a toron structure. Moreover, the current-driven topological transformation between hopfion and toron has also been realized in finite-sized nanostripes and stepped nanostructures. This deformation and transformation arise from the repulsive potential of the boundaries or edges. To connect real-space observations and 3D topological spin configurations, we simulate the Lorentz transmission electron microscope images of the aforementioned magnetic structures. This study, uncovering the dynamics and transformation of hopfions, will invigorate 3D magnetic structures-based memory and logic devices.

Softness Perception of Visual Objects Controlled by Touchless Inputs: The Role of Effective Distance of Hand Movements.

Feedback on the material properties of a visual object is essential in enhancing the users' perceptual experience of the object when users control the object with touchless inputs. Focusing on the softness perception of the object, we examined how the effective distance of hand movements influenced the degree of the object's softness perceived by users. In the experiments, participants moved their right hand in front of a camera which tracked their hand position. A textured 2D or 3D object on display deformed depending on the participant's hand position. In addition to establishing a ratio of deformation magnitude to the distance of hand movements, we altered the effective distance of hand movement, within which the hand movement could deform the object. Participants rated the strength of perceived softness (Experiments 1 and 2) and other perceptual impressions (Experiment 3). A longer effective distance produced a softer impression of the 2D and 3D objects. The saturation speed of object deformation due to the effective distance was not a critical determinant. The effective distance also modulated other perceptual impressions than softness. The role of the effective distance of hand movements on perceptual impressions of objects under touchless control is discussed.