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检索条件"任意字段=International Conference on Computer Graphics, Imaging and Visualization"

共 12087 条记录，以下是751-760 订阅

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A Visual Interaction Method for Ventilation Environment Coupled with BIM-CFD and Virtual Reality

A Visual Interaction Method for Ventilation Environment Coup...

引用

6th international conference on Intelligent Computing and Signal Processing (ICSP)

作者： Ting Liu Qun Zhang Mingjiang Wang Bin Li Power China Northwest Engineering Corporation Limited Xi'an China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

The traditional analysis results based on computational fluid dynamics (CFC) are presented in two- dimensional cloud maps, which makes the calculation process cumbersome and difficult for users to understand. With the development of virtual reality (VR) technology, new ideas have been provided for wind environment visualization. Currently, most of the coupling from CFD to VR visualization requires post- processing software such as Paraview, Autodesk 3DMax, Unity 3D, etc. for rendering or intermediate format conversion. This process is not only time-consuming, but also prone to data loss during model transformation, which affects the timely analysis and feedback of design results. This article combines Building Information Modeling (BIM) technology, establishes a parameterized 3D model, proposes a model lightweight processing method based on the three-dimensional grid method, and develops the FBX Export lightweight plugin to convert CFD simulation results into FBX format that can be integrated on the VR platform, simplifying the immersive visualization method of CFD results. Then, by improving the Lagrangian algorithm, the geometric model and CFD calculation results are visualized and displayed in the model rendering software. This process eliminates the need for CFD post-processing middleware, avoids unnecessary data exchange and software incompatibility issues, improves the quality of virtual visualization and environment rendering, and helps designers analyze ventilation environments in virtual 3D environments.

关键词： Couplings Solid modeling Three-dimensional displays Computational fluid dynamics Simulation Buildings Data visualization Virtual reality Ventilation Rendering (computer graphics)

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SynchroLearn: Master Deadlock and Synchronization Through Interactive Learning

SynchroLearn: Master Deadlock and Synchronization Through In...

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international conference on Computing and Networking Technology (ICCNT)

作者： G Bhavya Shreya Bhanot M Srinidhi Samreen Sidhu Sajitha Krishnan Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India Department of Computer Science & Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Today, educational tools have become necessary for learners to learn well and improve their knowledge. These tools complement knowledge as they can make it more vivid and add some simulation or game into the learning process. It is self-learning since the students can learn from any place and it also enables the students to go further on content that may interest them, and which may help them in the understanding of the concept. This paper takes the idea of developing SynchroLearn, which is an educational visualization tool developed with the help of HTML, CSS, and JavaScript that enables the teaching of deadlock handling techniques effectively for both the developers and the students. To expound on techniques such as the Producer-Consumer problem, Peterson’s method, Test-and-Set Lock, and the Dining Philosophers problem, an online tool known as SynchroLearn helps in providing the learner an actual time visualization. These strategies present several ways of handling resources, and with that, the management of their utilization process, so that the processes could be controlled in terms of what resources they require, which in turn, helps to solve and prevent such cases of deadlocks. This approach helps to learn complex relationships as well as to understand the interactions between the different processes, identify the deadlock situations, and use the essential methods for their resolution. They bring out the idea linking theoretical proficiencies and practical application by demonstrating them as simple-to-follow graphics which are therefore easier to implement.

关键词： visualization Education Process control Games System recovery Synchronization

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SSVEP Speller Implementations Across Desktop, Web, and Mobile Platforms

SSVEP Speller Implementations Across Desktop, Web, and Mobil...

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Brain computer Interface & Healthcare Technologies (iCon-BCIHT), international conference on

作者： Rohit Kumar Mishra Saumya Kushwaha Aakash Deep Harsh Koria Priyanka Jain Naveen Kumar Jain NC AI & XR C-DAC Delhi Delhi India C-DAC Delhi Delhi India

ISBN: (数字)9798331540067

ISBN: (纸本)9798331540074

This study explores the implementation of steady-state visual evoked potential (SSVEP) stimuli generation across various platforms to advance brain-computer interface (BCI) accessibility and usability. BCls provide assistive capabilities for people with diseases like spinal cord injury (SCI), Stroke, and Amyotrophic lateral sclerosis (ALS) by facilitating direct communication paths between the brain and external equipment Creating visual stimuli at specific frequencies to produce reliable neural responses is a basic challenge for BCls based on SSVEP. We ensured outstanding speed and device and browser synchronization by effectively rendering stimuli on web-based systems using WebGL. To create a seamless user experience, we combined WebGL with Web View for mobile devices, improving rendering speed and compatibility. Our work discusses the implementation of Psychopy and WebGL in providing reliable SSVEP stimuli through this multi-platform method. Comparative findings between desktop, online, and mobile implementations show how flexible and scalable our approach.

关键词： visualization Rendering (computer graphics) Mobile handsets Brain-computer interfaces User experience Steady-state Browsers Reliability Synchronization Usability

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A Robust Image Registration Using Multi-Scale Feature Extraction Techniques Using Deep Learning 4

A Robust Image Registration Using Multi-Scale Feature Extrac...

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4th international conference on Smart Electronics and Communication, ICOSEC 2023

作者： Madasamy, Sathiyakeerthi Nelson Kennedy Babu, C. Sumathi, V. Chokkalingam, Arun Pilvi Systems Inc Solution Architect LewisvilleTX75057 United States Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Tamil Nadu Chennai India Sri Sai Ram Engineering College Department of Mathematics Tamil Nadu Chennai44 India Rmk College of Engineering and Technology Department of Electronics and Communication Engineering Tamilnadu Chennai India

ISBN: (纸本)9798350300888

Image registration is a significant assignment in computer visualization and medical imaging, which involves aligning two or more descriptions of the same division or object taken from different viewpoints or at dissimilar epochs. Deep learning-based approaches have recently demonstrated promising outcomes in several image-processing applications, including image registration. Using multi-scale feature extraction methods and deep learning, the study provides a reliable image registration method in this study. Three primary steps make up the suggested method: feature extraction, feature matching, and transformation estimation. A deep convolutional neural network (CNN) is utilized in the feature extraction process to extract multi-scale information from the input images. The CNN architecture is built to manage large-scale deformations by extracting features at various scales. Following feature extraction, a strong matching technique based on the nearest neighbor distance ratio test is utilized to match the extracted features. The proposed method uses the Random Sample Consensus (RANSAC) algorithm to estimate the transformation parameters robustly, which helps to handle outliers and noise in the feature-matching process. The proposed method is assessed on several benchmark datasets, including the ETH-80 dataset and the TUM RGB-D dataset, and compared with state-of-the-art approaches. The investigational consequences demonstrate that the proposed method outstrips prevailing approaches in terms of accuracy and robustness, especially for images with large-scale deformations. The proposed technique also demonstrates good performance in the presence of noise and outliers, which further demonstrates its robustness. © 2023 IEEE.

关键词： Feature extraction

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Exploring Deep Feature Loss in Generative Adversarial Network for Satellite Image Resolution Enhancement

Exploring Deep Feature Loss in Generative Adversarial Networ...

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international conference on Electrical, computer and Communication Engineering (ECCE)

作者： Md. Sorwar Alam Rafiqul Islam Department of Computer Science and Engineering Dhaka University of Engineering & Technology Gazipur Bangladesh

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

Satellite imaging is an essential tool that is commonly utilized for agricultural development, environmental monitoring, urban planning, and many other applications. However, the poor resolution of satellite images makes it difficult to extract fine-grained features and prevents them from being used effectively. Several techniques, including unsupervised and supervised learning models, have been developed to address the challenges. In this paper, an efficient resolution improvement approach is proposed by tweaking the adversarial loss functions of a Generative Adversarial Network using deep neural network features. A lightweight MobileNet model is incorporated as backbone to improve adversarial loss functions for generating a high-resolution (HR) image from a low-resolution (LR) image. The proposed model is trained on pairs of LR and HR image datasets to map the LR image to its corresponding HR image. Then, extensive experiments are carried out to obtain HR images that are compared to some state-of-the-art models. The experimental results also investigated losses, indicating the effectiveness and improvement of the suggested approach for boosting satellite image resolution.

关键词： Training visualization Satellites Urban planning Transfer learning Superresolution imaging Generative adversarial networks Feature extraction Satellite images

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DeFVIS: Visual Analysis of Microscopic Parameters and Macroscopic Properties of Fluoropolymers 5

DeFVIS: Visual Analysis of Microscopic Parameters and Macros...

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5th international conference on Pattern Recognition and Artificial Intelligence, PRAI 2022

作者： Tian, Xiaokun Wu, Yadong Liu, Haoyu He, Zhouqiao Sichuan University of Science & Engineering College of Computer Science & Engineering Yibin China

ISBN: (数字)9781665499163

ISBN: (纸本)9781665499163

For the preparation of fluoropolymers, both process flow analysis and data analysis are needed. Meanwhile, the data sources for the study of fluoropolymer preparation are various, the production and characterization metrics are highly dimensional, and the parameters are unknown. Manual line-byline data analysis drastically restricts the effectiveness of analysts. This paper proposes DeFVIS, a visual analysis system for decoding fluorine materials, an interactive visual analysis system that proposes a multi-source data import and centralized storage technique;an adapted visualization model that encodes abstract preparation process data and high-dimensional metric data into intuitive graphics, thereby establishing an intuitive link from formulation to process to micro-polymer and macro-properties. Two case studies and user interviews demonstrate the efficiency and usability of DeFVIS. © 2022 IEEE.

关键词： Data fusion

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Image Restoration of Underwater Bubble Disturbance Based on Improved U-Net Network

Image Restoration of Underwater Bubble Disturbance Based on ...

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Advanced Information, Mechanical Engineering, Robotics and Automation (AIMERA), IEEE international conference on

作者： Yukun Wang Fan Ye Xiaobo Chen Juntong Xi School of Mechanical Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350343335

ISBN: (纸本)9798350343342

Distinct from typical underwater imaging, underwater imaging affected by underwater bubble disturbance blurs imaging information, thereby rendering the traditional underwater imaging model no longer being appropriate. We have proposed an improved U-Net network with excellent restoration efficiency and accuracy to weaken the underwater bubble influence. The linear activation function is adopted in our improved U-Net network, and corresponding experimental datasets are captured and processed for further training. Through the underwater restoration experiments, compared with underwater bubble disturbance conditions, our restoration model significantly improves the accuracy of underwater calibration, and subsequently provides a robust guarantee for underwater measurement applications.

关键词： Training Accuracy Atmospheric modeling Rendering (computer graphics) Mechanical variables measurement Cameras Image restoration Calibration Robotics and automation Mechanical engineering

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Low-Latency Immersive 6D Televisualization with Spherical Rendering 20

Low-Latency Immersive 6D Televisualization with Spherical Re...

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20th IEEE-RAS international conference on Humanoid Robots (HUMANOIDS)

作者： Schwarz, Max Behnke, Sven Univ Bonn Autonomous Intelligent Syst Grp Bonn Germany

ISBN: (纸本)9781728193724

We present a method for real-time stereo scene capture and remote VR visualization that allows a human operator to freely move their head and thus intuitively control their perspective during teleoperation. The stereo camera is mounted on a 6D robotic arm, which follows the operator's head pose. Existing VR teleoperation systems either induce high latencies on head movements, leading to motion sickness, or use scene reconstruction methods to allow re-rendering of the scene from different perspectives, which cannot handle dynamic scenes effectively. Instead, we present a decoupled approach which renders captured camera images as spheres, assuming constant distance. This allows very fast re-rendering on head pose changes while keeping the resulting temporary distortions during head translations small. We present qualitative examples, quantitative results in the form of lab experiments and a small user study, showing that our method outperforms other visualization methods.

关键词： visualization Head Robot vision systems Humanoid robots Reconstruction algorithms Cameras Rendering (computer graphics)

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Exploring Interaction Techniques for Navigating Medical Images Using a Motion-Tracked Pen

Exploring Interaction Techniques for Navigating Medical Imag...

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IEEE international conference on Serious Games and Applications for Health (SeGAH)

作者： Matthias Süncksen Sascha Reinhold Michael Teistler Center for Interaction Visualization and Usability (CIVU) Flensburg University of Applied Sciences Flensburg Germany

Medical imaging modalities like computer tomography or magnetic resonance imaging produce vast amounts of imaging data. For radiologists, whose tasks is to evaluate these images, work becomes increasingly burdensome, leading at times to occupational diseases like repetitive strain injury. Interacting with 3D patient data derived from the original 2D images is another challenge in human-computer-interaction. To simplify the handling of both 2D and 3D medical imaging, a motion-tracked pen-like input device is presented to explore novel interaction modes for medical imaging.

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3D Molecular Docking Study of Drug-Drug Interactions Between Antidepressants and Immunosuppressive Drugs

3D Molecular Docking Study of Drug-Drug Interactions Between...

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international conference on computer Supported Cooperative Work in Design

作者： Tie Hua Zhou Zheng Yang Zhang Ling Wang Xi Wei Wang School of Computer Science Northeast Electric Power University Jilin China

ISBN: (数字)9798331513054

ISBN: (纸本)9798331513061

Drug-Drug Interactions (DDIs) are an issue that cannot be ignored in clinical treatment. With the improvement of people's living standards and the evolution of the disease spectrum, the relationship between emotions and the immune system has gradually attracted attention. Among them, mood swings can significantly affect the function of the immune system, and disorders of the immune system may also cause mood disorders. Therefore, the interaction between antidepressants and immunosuppressive drugs has important research value. This article deeply analyzes the interaction strength of these two types of drugs to assess their potential risks, thereby optimizing treatment plans and reducing adverse reactions. At the same time, 3D imaging technology is used to more intuitively display the binding position and action intensity of drugs at the target, providing strong support for clinical decision-making and helping to achieve safer and more personalized combined treatment plans.

关键词： Proteins Three-dimensional displays Mood Federated learning Antidepressants Data visualization imaging Reliability engineering Standards Immune system

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