Texture Mapping Research Articles

The Development and Application of Computer-Assisted Painting Technology in the Convergence of Art and Technology

Abstract With the development of computer technology, digital painting has become more and more mature, which makes the whole creative process of painting more convenient, efficient, and diversified. This paper first introduces the definition, development history, and application of digital painting. A computerized painting model is created using knowledge representation, and the basic unit of the painting model is described. The paintbrush consists of hair filaments, each of which has its color tone and strokes. The brush’s movements are a result of position, pressure, and color tone, while the picture is a collection of strokes. Geometric transformations such as translation, rotation, and scaling are applied to the geometric information describing the strokes. This approach enables the simulation of painting effects, including the creation of scratches, color diffusion effects, texture mapping, and mutations on the strokes. This paper’s model enhances the painting skills of art students in six dimensions, achieving an efficiency evaluation score of 93 and a quality evaluation score of 96 in the abstract painting style. This model meets the realistic requirements for the advancement of computer-aided painting technology in art creation at a high level.

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.

RGB pixel information fusion segmentation of dense point cloud data for transmission and distribution 3D digital corridors

Abstract Point cloud segmentation, as a key link in 3D point cloud data processing, can realize power transmission and distribution positioning, object identification, classification, and feature extraction, which helps to refine power grid management. In this paper, firstly, dense point cloud transmission and distribution 3D digital corridor modeling is carried out. Alignment splicing and noise reduction are carried out after obtaining the original dense point cloud. Contour line extraction, geometric modeling, and texture mapping are realized after processing the data to ultimately realize the transmission and distribution of 3D digitization. Then, the conversion formula for the pixel coordinate system and world coordinate system is derived to extract features from point clouds. Finally, a distance-based feature fusion method is designed to extract spatial features from point clouds and use the joint attention layer to segment them by fusing RGB pixel information. The original dense point cloud of a transmission and distribution digital corridor is segmented using the model presented in this paper for application after testing the dataset. It is found that the under-segmentation ratio of this paper’s algorithm is 0.96%, 3.44%, and 2.87% for the three scenarios of regular, irregular, and multi-targets, respectively, which is much lower than that of RANSAC+ECS with FCM + ECS. The intersection and concatenation ratios of this paper’s algorithm for the scenarios of irregular geometry as well as multi-target objects are 91.49% and 89.56%. It is much higher than 64.31% and 72.17% for RANSAC + ECS and 76.85% and 60.91% for FCM + ECS, which illustrates that this paper’s algorithm has a significant advantage in performance. In this study, the target point cloud can be segmented with high accuracy from the dense point cloud of a 3D model of power transmission and distribution with a large amount of data, effectively avoiding the phenomenon of under-segmentation and over-segmentation and contributing to the accurate control of power grid data.

Virtual display and digital realization of furniture products

In this paper, the three-dimensional display system of furniture products combines the three-dimensional model and the image. Thus it can better show furniture products and their scenes in the shape of 3D in front of all users. In addition, the design of humanized interaction and artistic interface enhances the sense of reality and visual aesthetic in the process of the products browsing experience. According to the specific demand, this system chooses the method of three-dimensional transformation which uses two-dimensional graphics afterwards. At the same time, it uses the pictures of the real furniture products which are treated as mapping in order that model texture could realize the reality of the real furniture and improve the speed of the system in turn. Meanwhile, in order to simplify the mode, it makes use of LOD technology or a two-dimensional image as texture mapping.

Research on Visualization Teaching of Art and Design in Colleges and Universities Combining 3D Modeling Technology

Abstract This paper discusses constructing 3D modeling process for art and design works using 3D display technology and SIFT feature algorithm. Firstly, the pictures with different angles are obtained by changing the geometric information of the graphics and determining their positions in 3D space. Then the lighting model and texture mapping are used to enhance the realism, and the feature points are extracted in combination with the SIFT algorithm to determine the angle of the pictures. An initial 3D model is generated by image silhouette convergence, which corrects the image segmentation several times to complete the modeling. In addition, the study applies the modeling technique to the visualization teaching of art design, and verifies the teaching effect through students’ attitude and practical performance. The results show that most students have positive attitudes towards visualization teaching, especially in Class 2 and Class 15, where the favorite rate reaches 65%. Under this teaching method, students can flexibly utilize the design elements to create diversified art works.

Characteristic analysis of village cultural landscape by Lian Li space information technology and three-dimensional modelling

Abstract At present, due to the traditional village landscape protection method being relatively single, resulting in the traditional village landscape tends to “homogenization,” which is not conducive to the development of the village cultural landscape. This paper combines spatial information technology and three-dimensional modeling to reconstruct the village landscape and analyze its characteristics. Low-altitude oblique photography technology is used to collect village landscape information from multiple angles and then combined with the 3D model imaging law covariance equations to form the landscape 3D model features and then complete the multi-visual 3D model information matching. Finally, through texture mapping, the 3D model is generated to match the color of the real landscape. Using BIM technology, the data is refined to address the problem of local defects in the landscape 3D reconstruction process. The proposed technology is applied in practice to analyze the spatial comprehensibility of the test village landscape, and the comprehensibility value R² is obtained as 0.317, which is a poor spatial order of the test village. The village residents’ actual landscape color perception of the town ranges from -0.0364 to 0.4566, and the expected range is above 0.7. The actual perception is much lower than the predicted perception, and the subsequent landscape modification should be close to the villagers’ expectations.

Soil Texture and pH Mapping Using Remote Sensing and Support Sampling

Soil Texture and pH Mapping Using Remote Sensing and Support Sampling

Virtual Practice Teaching of Civics Classes in Colleges and Universities in the Context of Big Data Technology

Abstract In this study, we successfully realized the interaction design of virtual Civics teaching scene through multiresolution hierarchical detail (LOD) model, and constructed an immersive teaching environment using texture mapping technology. Combined with the gesture recognition and training of Adaboost classifier, this paper proposes an innovative interaction model for virtual Civics and Politics teaching. Through in-depth Analysis of the virtual interactive teaching elements of Civics courses in colleges and universities, this study conducted a covariance analysis of the aspects of creativity, critical thinking, metacognition, self-efficacy, and scientific ideological reasoning. Then it explored the effects of different places of origin and types of schools on the acceptance of virtual Civics courses by the students. It was found that among the science and engineering and teacher training students, the science and engineering students paid more attention to the virtual Civics teaching (3.36 and 3.05, respectively). In addition, compared with traditional Civics teaching, virtual practice teaching significantly increased students’ motivation (3.79), proving that Civics courses incorporating virtual interaction design have significant advantages in improving learning attractiveness.

Breakthroughs and Applications of Augmented Reality (AR) Technology in the Digital Media Field

Abstract This study pioneers the application of augmented reality (AR) in the realm of digital media, integrating AR technology with cultural education and artistic media concepts to forge a novel trajectory for digital media art creation. It delves into AR 3D scene construction technologies, employing calibration through the reconstruction of 2D image sequences, feature point extraction for spatial coordinate transformation, and 3D model development. Furthermore, it utilizes Level of Detail (LOD) models and texture mapping technologies to enhance visualization and interaction. The research culminates in a comparative analysis of traditional and AR-based media, evaluating differences in appeal and assessing functional capabilities. The findings indicate that AR-based media outperforms traditional media across several functions: media search (0.385), virtual design (0.424), immersive experience (0.466), real-time interaction (0.525), and user communication (0.396), with users expressing high satisfaction with these enhanced capabilities. This study not only diminishes the complexities associated with integrating digital media and AR technologies but also optimizes and innovates traditional methodologies.

Research on Rapid Parameterized Modeling of CityEngine in the Application of Smart Campus Platform

Currently, government departments in various regions are vigorously promoting the construction of smart cities. As a part of smart cities, quickly obtaining or creating three-dimensional spatial models of campuses is an important part of the basic framework of smart campus construction. Existing modeling methods have problems such as low modeling efficiency and difficult maintenance in the later stage. This article proposes a CGA (Computer Generated Architecture) parameterized 3D modeling method based on CityEngine, exploring the parameterized modeling rules of important modeling entities such as roads and buildings in university campuses. By expanding and customizing the modeling rules, campus road and building modeling rule templates are created. The results showed that the proposed method and texture mapping rules were used to achieve fast and accurate 3D scene modeling of the campus, avoiding a lot of repetitive modeling work and improving the efficiency of modeling work.

Visualization Challenges of Virtual Reality 3D Images in New Media Environments

Abstract This paper proposes a three-dimensional image visualization process to face-drawing three-dimensional image reconstruction algorithm to obtain the data field with three-dimensional space, using color adjustment based on global color correction and local Poisson fusion to optimize the splicing seams between the texture color blocks and updating the visualization technology of three-dimensional images. Divide the digital display design and create a virtual reality visualization display using 3D modeling in combination with the new media environment. Propose design steps to visualize virtual reality three-dimensional images in the new media environment by combining the key algorithms of three-dimensional image visualization from the previous section. Combined with the application of new media displaying 3D images, the concept of artifact shape in reconstructed images is proposed to analyze the quality of 3D image reconstruction by taking the Herman model and Sheep-Logan model as the research object. Test experiments are conducted to examine the visual impact of texture mapping algorithms, and different sampling intervals are set to measure the drawing time of 3D reconstruction. For the data size and number of pictures of other organizations, the processing time of the 3D image reconstruction algorithm based on surface drawing is no more than 2s. The denser the sampling points are, the higher the degree of fitting, the more complete the preservation of isosurface information is, the finer the effect of 3D reconstruction, and the higher the quality of the image.

Opportunities and Challenges of Artificial Intelligence + Enabling Museum Building

Abstract The explosive development of artificial intelligence technology greatly promotes the intelligent construction of museums and strengthens their cultural inheritance role. This paper takes artificial intelligence technology as its guide, analyzes the advantages of AI technology in the intelligent museum, and establishes the specific structure of an intelligent museum by combining VR technology. Wisdom Museum can realize the effective repair and presentation of cultural relics data. This paper uses three-dimensional laser scanning technology to obtain cultural relics point cloud data, repair the holes in the point cloud data through RBF, optimize the point cloud data by combining texture mapping, and input the optimized data into the GC-GAN model to realize the three-dimensional digital repair of cultural relics images. Moreover, the smart museum’s intelligent interaction system is built by combining virtual reality technology and related equipment. Taking Dunhuang mural point cloud data as an example, the number of point clouds of the RBF hole repair algorithm differs from the original data by only 5.86%, and the SSIM and PSNR values on the repaired portraits are 0.83 and 26.36 dB, respectively. The SUS total score for the user on the intelligent interactive system is 73.875, and the UEQ factor scores are averaged out at 1-3 points. The creation of a smart museum can be realized using AI technology, providing users with an immersive cultural relics viewing experience and activating the vitality of all kinds of cultural relics in the museum.

Practical Exploration of Smart Classroom in Piano Teaching

Abstract In this paper, texture mapping technology is utilized to enhance the virtual reality piano teaching situation, and the piano classroom teaching data is integrated through big data statistical analysis methods. A deep neural network based on BERT+BiLSTM+CRF is used to train a named entity recognition model and complete the construction of a knowledge graph for piano subject data. Then, deep learning methods are used to extract the piano subject data and construct a visualized knowledge graph for the piano subject. Analyze the use of the Piano Smart Classroom teaching platform and the development of a blended teaching mode. The design requirements of the piano intelligent teaching platform are planned from two aspects: platform user roles and platform use cases, and the overall design of the piano intelligent teaching platform is carried out. The use of piano teaching video samples is a tool for calculating the teaching language ratio, analyzing the teaching interactions between teachers and students, and comparing the number of interactions between traditional teaching and smart classroom teaching. Analyze the effectiveness of piano-smart classroom teaching in three dimensions: cognition, emotion, and skill. The mean value of the specific content score of piano intelligent classroom teaching is 3.82, which is the single item with the highest mean value, and the piano teaching classroom supported by smart technology can show the piano teaching content more comprehensively.

3D animation stereo space design based on digital visual communication technology

Abstract With the rapid development of science and technology, digital visual communication technology has become an important tool for 3D animation stereo space design. The study constructs a 3D animation stereo space design framework model using NURBS-based surface modeling and texture mapping algorithms. It compares it with the traditional 3D modeling algorithm to explore the authenticity and reliability of the stereo space design framework model for 3D animation. Finally, by comparing the differences in user experience between the 3D animated stereo spatial design framework model proposed in this paper and the spatial design of the traditional 3D modeling model, the user experience effect and superiority of the 3D animated stereo spatial design framework model are explored. After comparison, the detection time of the 3D stereo spatial design framework model in three-time indicators is 307ms, 324ms, and 318ms, respectively, which is significantly faster than the traditional 3D modeling algorithm. Its detection accuracy is 17% higher than that of the conventional 3D modeling algorithm, and the number of delays, scene stutters, and black screen flashes of the 3D stereo spatial design framework model and the traditional 3D modeling algorithm increase with the extension of detection time, but the former is always better than the latter. The 3D stereo spatial design framework model has a higher mean score than the traditional 3D modeling algorithm by 8.12 to 9.82 points in terms of user experience.

유물의 디지털 탁본에 대한 방법론 연구

The study of artifact rubbing methods has only been briefly mentioned in the fields of engineering and photography as a discussion of technical procedures and representations of visibility. However, recent research on artifact rubbings has marked a turning point in the discussion as it has been adapted to the digital age. As previous methods of drawing artifacts, such as measuring and tracing, have been digitized, manual rubbing has begun to be replaced. In the process, there have been discussions on digital methodologies for measuring and tracing artifacts, but there has been a lack of discussion on the application of digital methods for rubbing. Some research on digital applications of rubbing has focused on the mapping of scanned modeling materials of artifacts from a technical perspective. Nowadays, the application of algorithms through artificial intelligence is leading to tangible research on tablets. However, it has not yet advanced as a research topic. Recognizing this problem, this paper discusses the transition to the digital application of rubbing and its methodology. In particular, we aimed to show how it can be applied to investigations and research beyond the existing technical process of rubbing, and how to optimize it.
 The process of digital rubbing was applied in two main ways. The first is to visualize the mapping results through the existing AO map texture extraction method as an image, and the second is to produce original artifacts in the form of high polygon and low polygon artifacts to map and visualize black and white textures. In order to extract the optimal tabletop image, the low-polygon artifact is smoothed to provide an appropriate numerical criterion. The digital tabletop material was then used to flatten and expand the tabletop image by applying the Streching technique, and the image was imaged to provide a direction for the editorial drawings of the report.

Research on the Digital Preservation of Intangible Cultural Heritage of Folk Dance Art Category

Abstract In this paper, based on the rapid head generation technique of the model library, we obtain a frontal 2D face photo, mark 13 feature points selected from 7 parts, such as both eyes, nose, mouth, etc., to determine the approximate position of the whole facial features, simulate the real color of the face according to the texture mapping of the face, and at the same time, we add the texture features of the target face in the to the matching model, to achieve the mapping of overlaying texture to the neutral texture and the fusion of skin color. Using HigherHRNet network extraction to obtain the coordinate information of the joint points of the intangible cultural heritage dance inheritors and their heat maps, the obtained key frames of the dance features are connected in a certain order to obtain the synthesized folk dance video with gesture estimation. Combining semantic segmentation of keyframes and style rendering, the visual image of the dance is designed, and the intangible cultural heritage of folk dance is analyzed through examples. The results show that this paper’s method achieves more than 90% recognition accuracy on all three datasets and more than 94.8% recognition accuracy on the folk dance movement dataset. On the evaluation of folk dance movements, the average distance calculated by this paper’s algorithm is the largest, 95.7, and the average score is the lowest, 43.6. The average distance and average score of this paper’s algorithm are in between the above two cases, i.e., the experimental results verify the effectiveness of this paper’s method. This study promotes the intelligent protection and creative inheritance of Chinese non-heritage dances through digital protection.

Research on Distributed Virtual Reality Technology Based on VIRTOOLS in the Context of Big Data

Abstract In this paper, virtual reality development software Virtools is used as the main tool for scene rendering in distributed virtual reality systems. The nearest distance-based control strategy is designed to achieve synchronous interaction between nodes by utilizing consistency control and prediction algorithms for nodes in the same cluster. Optimize the virtual scene by using texture mapping, detail level, and dynamic loading techniques. Propose a distributed parallel drawing method based on image plane segmentation to accelerate image drawing. The analysis and testing of the multiuser virtual reality roaming system in this paper is completed from four aspects: offline training model evaluation amount roaming test, lock performance test, and operation sequence error correction test. Among the analyzed data, the average lock time overhead is 123us, which has no obvious connection with the number of nodes, the number of locking times, and the execution of operations. According to each lock overhead of 123us, the number of concurrencies allowed per second is 8563, which fully meets the requirements of the system at this stage.

TwinTex: Geometry-Aware Texture Generation for Abstracted 3D Architectural Models

Coarse architectural models are often generated at scales ranging from individual buildings to scenes for downstream applications such as Digital Twin City, Metaverse, LODs, etc. Such piece-wise planar models can be abstracted as twins from 3D dense reconstructions. However, these models typically lack realistic texture relative to the real building or scene, making them unsuitable for vivid display or direct reference. In this paper, we present TwinTex , the first automatic texture mapping framework to generate a photorealistic texture for a piece-wise planar proxy. Our method addresses most challenges occurring in such twin texture generation. Specifically, for each primitive plane, we first select a small set of photos with greedy heuristics considering photometric quality, perspective quality and facade texture completeness. Then, different levels of line features (LoLs) are extracted from the set of selected photos to generate guidance for later steps. With LoLs, we employ optimization algorithms to align texture with geometry from local to global. Finally, we fine-tune a diffusion model with a multi-mask initialization component and a new dataset to inpaint the missing region. Experimental results on many buildings, indoor scenes and man-made objects of varying complexity demonstrate the generalization ability of our algorithm. Our approach surpasses state-of-the-art texture mapping methods in terms of high-fidelity quality and reaches a human-expert production level with much less effort.

Surveying and mapping of large-scale 3D digital topographic map based on oblique photography technology

In the fields of geographic information systems and cartography, accurate topographic maps are crucial. Although traditional topographic mapping methods have certain accuracy, they have limitations in capturing features and building details. Therefore, this article proposes a large-scale 3D digital terrain mapping method based on oblique photography technology. Firstly, the UAV route is planned and image control points are arranged, to collect large-scale geographical object data by using UAV oblique photography technology. Then Smart 3D software is used to complete the 3D modeling of real large-scale topographic map through data preprocessing, air-to-air survey, control point import, 3D modeling, texture mapping and other steps based on the obtained geographical object data. The 2D and 3D linkage integrated mapping mode is adopted to obtain geomorphic information and elevation information, complete the data collection of indoor features, confirm the features that cannot be read on both sides of the indoor industry, complete the field supplementary mapping and adjustment, and realize the mapping of large-scale 3D digital topographic map. The experimental results show that this method can use oblique photography technology to collect data and establish a three-dimensional model of large-scale 3D digital terrain maps. The mean square error of accuracy detection is 0.202m, the mean square error of elevation is 0.257m, the mean square error of plane is 0.201m, and the mean square error of elevation is 0.197m. It has high drawing accuracy and excellent aerial triangulation performance.

Fine Detailed Texture Learning for 3D Meshes with Generative Models.

This paper presents a method to achieve fine detailed texture learning for 3D models that are reconstructed from both multi-view and single-view images. The framework is posed as an adaptation problem and is done progressively where in the first stage, we focus on learning accurate geometry, whereas in the second stage, we focus on learning the texture with a generative adversarial network. The contributions of the paper are in the generative learning pipeline where we propose two improvements. First, since the learned textures should be spatially aligned, we propose an attention mechanism that relies on the learnable positions of pixels. Secondly, since discriminator receives aligned texture maps, we augment its input with a learnable embedding which improves the feedback to the generator. We achieve significant improvements on multi-view sequences from Tripod dataset as well as on single-view image datasets, Pascal 3D+ and CUB. We demonstrate that our method achieves superior 3D textured models compared to the previous works. Please visit our web-page for 3D visuals.: https://research.nvidia.com/labs/adlr/textured-3d-learning.