scholarly journals A High-Resolution Texture Mapping Technique for 3D Textured Model

2018 ◽  
Vol 8 (11) ◽  
pp. 2228 ◽  
Author(s):  
Jiing-Yih Lai ◽  
Tsung-Chien Wu ◽  
Watchama Phothong ◽  
Douglas Wang ◽  
Chao-Yaug Liao ◽  
...  
Keyword(s):  
3D Model ◽  
Three Dimensional ◽  
Texture Mapping ◽  
Mapping Technique ◽  
High Quality ◽  
Mesh Parameterization ◽  
Mesh Partitioning ◽  
Blending Process ◽  
Box Method ◽  
Texture Size

We proposed a texture mapping technique that comprises mesh partitioning, mesh parameterization and packing, texture transferring, and texture correction and optimization for generating a high-quality texture map of a three-dimensional (3D) model for applications in e-commerce presentations. The main problems in texture mapping are that the texture resolution is generally worse than in the original images and considerable photo inconsistency exists at the transition of different image sources. To improve the texture resolution, we employed an oriented boundary box method for placing mesh islands on the parametric (UV) map. We also provided a texture size that can keep the texture resolution of the 3D textured model similar to that of the object images. To improve the photo inconsistency problem, we employed a method to detect and overcome the missing color that might exist on a texture map. We also proposed a blending process to minimize the transition error caused by different image sources. Thus, a high-quality 3D textured model can be obtained by applying this series of processes for presentations in e-commerce.

scholarly journals HIGH QUALITY TEXTURE MAPPING PROCESS AIMED AT THE OPTIMIZATION OF 3D STRUCTURED LIGHT MODELS

2019 ◽  
Vol XLII-2/W9 ◽  
pp. 389-396 ◽  
Author(s):  
L. Inzerillo ◽  
F. Di Paola ◽  
Y. Alogna
Keyword(s):  
Texture Mapping ◽  
Environmental Parameters ◽  
Image Resolution ◽  
Semantic Interpretation ◽  
High Quality ◽  
Mapping Procedure ◽  
Mesh Parameterization ◽  
3D Texture ◽  
Mesh Partitioning ◽  
Mapping Process

<p><strong>Abstract.</strong> This article presents the evaluation of a pipeline to develop a high-quality texture mapping implementation which makes it possible to carry out a semantic high-quality 3D textured model. Due to geometric errors such as camera parameters or limited image resolution or varying environmental parameters, the calculation of a surface texture from 2D images could present several color errors. And, sometimes, it needs adjustments to the RGB or lightness information on a defined part of the texture. The texture mapping procedure is composed of mesh parameterization, mesh partitioning, mesh segmentation unwraps, UV map and projection of island, UV layout optimization, mesh packing and mesh baking. The study focuses attention to the mesh partitioning that essentially assigns a weight to each mesh, which reveals a mesh’s weight calculated by considering the flatness and distance of the mesh with respect to a chart. The 3D texture mapping has been developed in <i>Blender</i> and implemented in <i>Python</i>. In this paper we present a flowchart that resumes the procedure which aims to achieve a high-quality mesh and texture 3D model starting from the 3D <i>Spider</i> acquire, integrated with the <i>SfM</i> texture and using the texture mapping to reduce the color errors according to a semantic interpretation.</p>

Design Modification of Additive Manufacturing Parts Using Texture Information of 3D Model

2019 ◽  
Vol 825 ◽  
pp. 19-30
Author(s):  
Tsung Chien Wu ◽  
Jiing Yih Lai ◽  
Yu Wen Tseng ◽  
Chao Yaug Liao ◽  
Ju Yi Lee
Keyword(s):  
Additive Manufacturing ◽  
3D Model ◽  
Three Dimensional ◽  
Texture Mapping ◽  
3D Models ◽  
Surface Shape ◽  
Design Features ◽  
Design Modification ◽  
Texture Information ◽  
Triangular Model

Additive manufacturing (AM) has been commonly used for the prototyping of three-dimensional (3D) models. The input model of the AM technology is a triangular model representing the surface shape of an object. The design features on a triangular model are generally not clear as the vertices are irregularly distributed. If design modification is necessary, it is difficult to segment and extract the meshes from the model. The objective of this study is to propose a method for extracting the design features on an object model by using the texture information. A 3D color model including a triangular model representing the object shape and a texture map describing the object texture is employed. The 3D model is generated by using a set of object images captured from different views surrounding the object. A texture mapping algorithm is then employed to generate the texture map corresponding to the 3D model. With both meshes and texture displayed in a texture mode, a region extraction technique is employed to extract the design features. All parts separated can then be fabricated with an AM machine, and assembled for checking the feasibility of design modification. Several products are employed to demonstrate the feasibility of the proposed technique.

scholarly journals 3D textile reconstruction based on KinectFusion and synthesized texture

2017 ◽  
Vol 29 (6) ◽  
pp. 793-806 ◽  
Author(s):  
PengPeng Hu ◽  
Taku Komura ◽  
Duan Li ◽  
Ge Wu ◽  
Yueqi Zhong
Keyword(s):  
Artificial Intelligence ◽  
Design Methodology ◽  
3D Model ◽  
Three Dimensional ◽  
Experimental Results ◽  
High Quality ◽  
Content Type

Purpose The purpose of this paper is to present a novel framework of reconstructing the 3D textile model with synthesized texture. Design/methodology/approach First, a pipeline of 3D textile reconstruction based on KinectFusion is proposed to obtain a better 3D model. Second, “DeepTextures” method is applied to generate new textures for various three-dimensional textile models. Findings Experimental results show that the proposed method can conveniently reconstruct a three-dimensional textile model with synthesized texture. Originality/value A novel pipeline is designed to obtain 3D high-quality textile models based on KinectFusion. The accuracy and robustness of KinectFusion are improved via a turntable. To the best of the authors’ knowledge, this is the first paper to explore the synthesized textile texture for the 3D textile model. This is not only simply mapping the texture onto the 3D model, but also exploring the application of artificial intelligence in the field of textile.

Flash Sliver Prevents Laser Penetrating Organic Materials

2012 ◽  
Vol 263-266 ◽  
pp. 48-52 ◽  
Author(s):  
Fu Ping Wang ◽  
Wei Fan ◽  
Sen Su ◽  
Sheng Xiong Liu ◽  
Zhi Yong Yin
Keyword(s):  
Organic Material ◽  
3D Model ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Sodium Stearate ◽  
Point Clouds ◽  
High Accuracy ◽  
Surface Point ◽  
Important Work ◽  
High Quality

High-quality point clouds are the bases of high-accuracy three-dimensional (3D) model. How to obtain the corresponding surface point clouds is always an important work in reverse engineering. Faro Laser Scanner Fonton120 was used to scan an organic material which is composed of potassium stearate, sodium stearate, polyvinyl alcohol and paraffin liquid in a dark room. The organic material has fewer reflectors and is penetrated by laser of scanner. For increasing the reflector and obtaining high-accuracy 3D model, the flash sliver was coated on organic material’s surface. Flash sliver was found not only increasing the high reflector but also preventing laser penetrating. It indicated that coating flash sliver was an efficient method to obtain high-quality point clouds. These findings have supplied a basis for 3D laser scanner appling to the field of organic material.

Three Dimensional Reconstruction of Coronary Arteries by Using Registration and Texture-Mapping onto Epicardial Surface on Nuclear 3D Image

2003 ◽  
Vol 03 (04) ◽  
pp. 567-587 ◽  
Author(s):  
Ryo Haraguchi ◽  
Naozo Sugimoto ◽  
Shigeru Eiho ◽  
Yoshio Ishida
Keyword(s):  
Coronary Arteries ◽  
Three Dimensional ◽  
Texture Mapping ◽  
Mapping Technique ◽  
Surface Model ◽  
Clear Understanding ◽  
3D Image ◽  
Three Dimensional Reconstruction ◽  
Dimensional Reconstruction ◽  
Matching Degree

This paper deals with a new method of three dimensional reconstruction of coronary arteries, by using the texture-mapping technique on a myocardial nuclear image. The bi-plane CAG images are texture-mapped onto a LV surface model which is pre-determined on a nuclear 3D image. By maximizing a matching degree between two mapped CAG images, registration between CAG and nuclear image is performed automatically. By taking only true images from the mapped CAG images, we can obtain 3D reconstructed coronary image on the LV surface model. This method has the great advantage that it is not necessary to extract the feature points, nor is there a need to identify the correspondence. The obtained images give us a clear understanding of the relation between the coronary artery and the function of the myocardium.

Etch Rate Modeling in MEMS Design

1996 ◽  
Author(s):  
Ted J. Hubbard ◽  
Erik K. Antonsson
Keyword(s):  
Etch Rate ◽  
3D Model ◽  
Three Dimensional ◽  
Wet Etching ◽  
Experimental Measurements ◽  
High Quality ◽  
Arbitrary Plane ◽  
Rate Behavior ◽  
Etch Rates ◽  
The One

Abstract This paper presents a model for determining the full three dimensional etch rate behavior of bulk wet etching of silicon from experimentally determined etch rates of four principal planes: (100), (110), (111), and (311). The etch rate for an arbitrary plane is expressed in terms of the measured planes. The model shows excellent agreement with both experimental measurements and values reported in the literature. For MEMS CAD to be able to accurately predict etched shapes, a high quality 3D model of etch rates such as the one reported here is required.

scholarly journals A Texture Selection Approach for Cultural Artifact 3D Reconstruction Considering Both Geometry and Radiation Quality

2020 ◽  
Vol 12 (16) ◽  
pp. 2521
Author(s):  
Shirui Hu ◽  
Zhiyuan Li ◽  
Shaohua Wang ◽  
Mingyao Ai ◽  
Qingwu Hu
Keyword(s):  
3D Reconstruction ◽  
3D Model ◽  
Evaluation Model ◽  
Texture Mapping ◽  
Cultural Artifacts ◽  
Radiation Quality ◽  
High Quality ◽  
Bronze Wares ◽  
Dense Matching ◽  
Selection Approach

3D reconstruction of culture artifacts has great potential in digital heritage documentation and protection. Choosing the proper images for texture mapping from multi-view images is a major challenge for high precision and high quality 3D reconstruction of culture artifacts. In this study, a texture selection approach, considering both the geometry and radiation quality for 3D reconstruction of cultural artifacts while using multi-view dense matching is proposed. First, a Markov random field (MRF) method is presented to select images from the best angle of view among texture image sets. Then, an image radiation quality evaluation model is proposed in the virtue of a multiscale Tenengrad definition and brightness detection to eliminate fuzzy and overexposed textures. Finally, the selected textures are mapped to the 3D model under the mapping parameters of the multi-view dense matching and a semi-automatic texture mapping is executed on the 3DMax MudBox platform. Experimental results with two typical cultural artifacts data sets (bronze wares and porcelain) show that the proposed method can reduce abnormal exposure or fuzzy images to yield high quality 3D model of cultural artifacts.

An experience of elaboration and implementation of systems of slag-forming mixtures mechanized feeding into CCM moulds

2020 ◽  
Vol 76 (10) ◽  
pp. 994-1003
Author(s):  
S. P. Eron’ko ◽  
M. Yu. Tkachev ◽  
E. V. Oshovskaya ◽  
B. I. Starodubtsev ◽  
S. V. Mechik
Keyword(s):  
Economic Effect ◽  
Three Dimensional ◽  
Movable Part ◽  
High Quality ◽  
Working Zone ◽  
Fine Material ◽  
Mixing Chamber ◽  
Field Samples ◽  
Technical Solutions ◽  
Feeding Systems

Effective application of slag-forming mixtures (SFM), being fed into continuous castingg machine (CCM) moulds, depends on their even distribution on the melt surface. Manual feeding of the SFM which is widely usedd does not provide this condition, resulting in the necessity to actualize the work to elaborate systems of SFM mechanized feedingg into moulds of various types CCM. A concept of the designing of a system of SFM feeding into CCM moulds presented with the ratte strictly correspondent to the casting speed and providing formation of an even layer of fine material of given thickness on the whoole surface of liquid steel. The proposed methods of designing of the SFM mechanized feeding systems based on three-dimensional computer simulation with the subsequent verification of the correctness of the adopted technical solutions on field samples. Informattion is presented on the design features of the adjusted facilities intended for continuous supply of finely granulated and powder mixtuures on metal mirror in moulds at the production of high-quality billets, blooms and slabs. Variants of mechanical and pneumo-mechaanical SFM supply elaborated. At the mechanical supply the fine material from the feeding hopper is moved at a adjusted distance bby a rigid horizontally located screw. At the pneumo-mechanical supply the metered doze of the granular mixture is delivered by a sshort vertical screw, the lower part of which is located in the mixing chamber attached from below to the hopper and equipped with ann ejector serving for pneumatic supply of the SFM in a stream of transporting gas. It was proposed to use flexible spiral screws in the ffuture facilities of mechanical SFM feeding. It will enable to eliminate the restrictions stipulated by the lack of free surface for locatiion of the facility in the working zone of the tundish, as well as to decrease significantly the mass of its movable part and to decreaase the necessary power of the carriage moving mechanism driver. The novelty of the proposed technical solutions is protected by thhree patents. The reduction of 10–15% in the consumption of slag-forming mixtures during the transition from manual to mechanizeed feeding confirmed. The resulting economic effect from the implementation of technical development enables to recoup the costs inncurred within 8–10 months.

scholarly journals Direct 3D model extraction method for color volume images

2021 ◽  
Vol 29 ◽  
pp. 133-140
Author(s):  
Bin Liu ◽  
Shujun Liu ◽  
Guanning Shang ◽  
Yanjie Chen ◽  
Qifeng Wang ◽  
...  
Keyword(s):  
3D Model ◽  
Clinical Medicine ◽  
Three Dimensional ◽  
Laplacian Matrix ◽  
Segmentation Method ◽  
Human Organs ◽  
Model Segmentation ◽  
Treatment Objective ◽  
Organ Models ◽  
Different Parts

BACKGROUND: There is a great demand for the extraction of organ models from three-dimensional (3D) medical images in clinical medicine diagnosis and treatment. OBJECTIVE: We aimed to aid doctors in seeing the real shape of human organs more clearly and vividly. METHODS: The method uses the minimum eigenvectors of Laplacian matrix to automatically calculate a group of basic matting components that can properly define the volume image. These matting components can then be used to build foreground images with the help of a few user marks. RESULTS: We propose a direct 3D model segmentation method for volume images. This is a process of extracting foreground objects from volume images and estimating the opacity of the voxels covered by the objects. CONCLUSIONS: The results of segmentation experiments on different parts of human body prove the applicability of this method.

scholarly journals Generation and Annotation of Simulation-Real Ship Images for Convolutional Neural Networks Training and Testing

2021 ◽  
Vol 11 (13) ◽  
pp. 5931
Author(s):  
Ji’an You ◽  
Zhaozheng Hu ◽  
Chao Peng ◽  
Zhiqiang Wang
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Image Annotation ◽  
Three Dimensional ◽  
Image Data ◽  
Detection Algorithm ◽  
Simulation Software ◽  
High Quality ◽  
Annotation Method ◽  
Detection Of Objects

Large amounts of high-quality image data are the basis and premise of the high accuracy detection of objects in the field of convolutional neural networks (CNN). It is challenging to collect various high-quality ship image data based on the marine environment. A novel method based on CNN is proposed to generate a large number of high-quality ship images to address this. We obtained ship images with different perspectives and different sizes by adjusting the ships’ postures and sizes in three-dimensional (3D) simulation software, then 3D ship data were transformed into 2D ship image according to the principle of pinhole imaging. We selected specific experimental scenes as background images, and the target ships of the 2D ship images were superimposed onto the background images to generate “Simulation–Real” ship images (named SRS images hereafter). Additionally, an image annotation method based on SRS images was designed. Finally, the target detection algorithm based on CNN was used to train and test the generated SRS images. The proposed method is suitable for generating a large number of high-quality ship image samples and annotation data of corresponding ship images quickly to significantly improve the accuracy of ship detection. The annotation method proposed is superior to the annotation methods that label images with the image annotation software of Label-me and Label-img in terms of labeling the SRS images.

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