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

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Architectural visualization using Augmented Reality

Architectural Visualization using Augmented Reality

引用

Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE), international conference

作者： Nikhil Raj Hema P Menon Abhinand Satheesh Naveen Nikhil A. P Vishnuraj K. R Department of Computer Science and Engineering Sreepathy Institute of Management and Technology Vavannor Palakkad Kerala

ISBN: (数字)9798331515911

ISBN: (纸本)9798331515928

In the dynamic field of architectural design, effective communication stands as a requirement for successful project realization. However, traditional 2D methods often struggle to convey the depth and essence of architectural visions to stakeholders. Augmented Reality (AR) emerges as a revolutionary tool, poised to transform architectural communication and stakeholder engagement. This work is an exploration of the transformative power of Augmented Reality in architectural design communication, employing a comprehensive methodology. By leveraging state-of-the-art technological innovations, the aim is to provide architects and designers with groundbreaking tools to translate their blueprints into immersive, dynamic experiences. Beginning with collaborative requirement analysis, conceptual design, and data acquisition, the optimization of assets for AR rendering follows suit. Augmented Reality, in tandem with Unity 3D, Figma, and specifically smartphones as AR devices are used for realization of the work. This integration fosters collaborative, immersive design experiences and propels architectural discourse into a new era of interactive visualization and communication.

关键词： Technological innovation visualization Three-dimensional displays Collaboration Transforms Rendering (computer graphics) Stakeholders Augmented reality Standards Smart phones

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3D visualization with VR Interaction for HPR1000 Design V&V Platform 2

3D Visualization with VR Interaction for HPR1000 Design V&V ...

引用

2nd IEEE international conference on Electronic Technology, Communication and Information, ICETCI 2022

作者： Zhang, Fan Zhou, Zhi China Nuclear Power Operation Cnnc Nuclear Industry Simulation Technology Key Lab Wuhan China

ISBN: (数字)9781728181158

ISBN: (纸本)9781728181158

Currently the HPR1000 design v&v (verification and validation) platform basically uses 2D visualization method to demonstrate results, which cannot meet the design and validation demands for different professional and technical personnel. And the v &v engineers cannot experience the operating environment with vivid inception. This paper proposes a VR based 3D visualization suggestion for the HPR1000 design v &v platform. Firstly, this paper describes the 3D visualization of the MCR. Then describes the human body signal input and response suggestion. The following part demonstrates the interactive suggestion and finally gives conclusions on the feasibility of different solutions. So the suggestion proposed in this paper can better help design the operation and maintenance technology and improve the operating experience, at the same time it ensures the accuracy and precision of design v &v results. © 2022 IEEE.

关键词： Three dimensional computer graphics

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Video Coding for Machines Based on Motion Assisted Saliency Analysis 12th

Video Coding for Machines Based on Motion Assisted Salienc...

引用

12th international conference on Image and graphics, ICIG 2023

作者： Chen, Hui Xu, Yuanyuan Key Laboratory of Water Big Data Technology of Ministry of Water Resources Hohai University Nanjing211100 China College of Computer and Information Hohai University Nanjing211100 China

ISBN: (纸本)9783031463105

With an increasing amount of video content analyzed automatically by computer vision algorithms, video coding for machines has received growing attention. With saliency analysis for machine vision, video coding scheme can be designed to preserve key information for machine tasks during compression. In this paper, based on versatile video coding (VVC), we propose a video coding scheme for machines using motion assisted saliency analysis. Taking multi-object tracking as an example task, Grad-CAM, a deep learning visualization method, is used to conduct saliency analysis for key video frames. Considering the complexity of saliency analysis and to improve association performance of multi-object tracking, a motion assisted saliency analysis has been designed for non-key frames, whose saliency maps are predicted using motion vectors and saliency maps of key frames. With saliency maps of all the frames, a coding tree unit (CTU)-level QP adjustment scheme has been derived, which prioritizes salient regions concerning machine vision during bitrate allocation. Experimental results show that, compared with VVC, the proposed scheme can achieve at least 20.3% of bitrate saving with the same tracking accuracy. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： computer vision

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Brain tumors classification from MRI images: A comparative study between different neural networks 28

Brain tumors classification from MRI images: A comparative s...

引用

28th international DMS conference on visualization and Visual Languages, DMSVIVA 2022

作者： Breve, Bernardo Caruccio, Loredana Cimino, Gaetano Cirillo, Stefano Iuliano, Gianpaolo Polese, Giuseppe Department of Computer Science University of Salerno Italy

ISBN: (纸本)1891706551

The detection of brain tumors through the analysis of images is becoming increasingly common for promptly treating patients. Among the different types of imaging techniques, Magnetic Resonances imaging (MRI) is probably the most popular one in the pre- and post-treatment to estimate the structure of tumors. Thus, they also represent a useful means for supporting intelligent techniques in the identification of brain tumors, enabling machine learning models to completely automate the classification task. In this paper, we propose a new methodology for classifying brain tumors through the analysis of MRI images. In particular, our approach relies on a feature extraction technique to obtain representative data, which are used as input for two predictive models, a Convolutional Neural Network (CNN) and a Residual Neural Network (ResNet). We discuss experimental evaluation performed over a ground-truth dataset and show a comparative analysis between proposed models in the classification of tumors according to their type. © 2022 by KSI Research Inc. and Knowledge Systems Institute, USA.

关键词： Magnetic resonance imaging

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Detection of Anomalous Components in Spatial Surveys Based on a Multidimensional Model of Poisson Flows and their Cognitive visualization 25

Detection of Anomalous Components in Spatial Surveys Based o...

引用

25th international conference on Soft Computing and Measurements, SCM 2022

作者： Gorokhov, Vladimir L. Brusakova, Irina A. Saint Petersburg Electrotechnical University LETI Department of Innovation Management St. Petersburg Russia

ISBN: (纸本)9781665496698

The paper proposes a technique for detecting anomalous components in spatial scans of multidimensional data in the tasks of multidimensional reviews in GIS technologies. Detection of anomalous components is carried out on the basis of unbiased algorithms under conditions of deep a priori uncertainty regarding the parameters of the distributions of survey data. The results of the detection are controlled by means of cognitive computer graphics. The methods are used to process multidimensional data of astronomical observations. These methods are very successfully applied in astrophysics and can be used for a wide range of tasks in BIG DATA. The methodology of such a combination can also be focused on the identification and forecasting of emergency situations in complex systems. © 2022 IEEE.

关键词： Surveys

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Segmentation of Different Human Organs on 3D computer Tomography and Magnetic Resonance imaging using an Open Source 3D U-Net Framework 23

Segmentation of Different Human Organs on 3D Computer Tomogr...

引用

23rd international Carpathian Control conference (ICCC)

作者： Popa, Didi-Liliana Popa, Radu-Teodoru Barbulescu, Lucian-Florentin Ivanescu, Renato-Constantin Mocanu, Mihai-Lucian Univ Craiova Fac Automat Comp & Elect Craiova Romania

ISBN: (纸本)9781665466363

Medical segmentation represents a method to delineate the borders of internal human organs on acquired 3D computer Tomography or MRI images, which are the most currently used imaging modalities. The U-net represents a deep neural network architecture that has the basic structure consisting in two paths and can be used for medical image segmentation. For U-Net Framework implementation we used Monai Toolkit from Kitware Inc, which is a PyTorch-based, open-source framework for deep learning in healthcare imaging used to create advanced training workflows and provides deep learning models. As input data we used two types of internal organs acquired with two image modalities:3D CT and *** visualization we used an in-house VTK based 3D Volume visualization Application *** the manual segmentation of the training datasets we used an open source segmentation application ITK-SNAP. Our results shows that the U-Net segmentation method delivers good final results and that is represents an robust method to segment internal organs.

关键词： DenseNet CNN U-Net Medical Segmentation Deep Neural Networks

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VU-NET: An Explainable AI Approach For Liver Segmentation

VU-NET: An Explainable AI Approach For Liver Segmentation

引用

international conference on Computing and Networking Technology (ICCNT)

作者： Ramakrishnananda Pranjal Singh Katiyar Rosy Sarmah Department of Computer Science and Engineering Tezpur University Tezpur Assam India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Medical image segmentation, particularly in tumor identification, is a critical aspect of modern healthcare. In this study, we propose our own VU-Net model to address liver tumor segmentation, utilizing the LiTS17 dataset and GradCAM visualization to provide insights into the model’s decision-making. Our contributions include a fine-tuned VU-Net model, extensive performance evaluation, and application of Grad-CAM for interpretability. These findings enhance understanding of deep learning models in medical imaging, promising advancements in tumor segmentation methodologies and contributing to improved patient care.

关键词： Performance evaluation Image segmentation visualization Image analysis Refining Liver computer architecture Medical services Tumors Biomedical imaging

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A Multi-modal Registration and visualization Software Tool for Artworks Using CraquelureNet 1

引用

26th international conference on Pattern Recognition, ICPR 2022

作者： Sindel, Aline Maier, Andreas Christlein, Vincent Pattern Recognition Lab FAU Erlangen-Nürnberg Erlangen Germany

ISBN: (数字)9783031377310

ISBN: (纸本)9783031377303

For art investigations of paintings, multiple imaging technologies, such as visual light photography, infrared reflectography, ultraviolet fluorescence photography, and x-radiography are often used. For a pixel-wise comparison, the multi-modal images have to be registered. We present a registration and visualization software tool, that embeds a convolutional neural network to extract cross-modal features of the crack structures in historical paintings for automatic registration. The graphical user interface processes the user’s input to configure the registration parameters and to interactively adapt the image views with the registered pair and image overlays, such as by individual or synchronized zoom or movements of the views. In the evaluation, we qualitatively and quantitatively show the effectiveness of our software tool in terms of registration performance and short inference time on multi-modal paintings and its transferability by applying our method to historical prints. © 2023, Springer Nature Switzerland AG.

关键词： visualization

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Research on a Method for Realizing Three-Dimensional Real-Time Cloud Rendering Based on Cesium

Research on a Method for Realizing Three-Dimensional Real-Ti...

引用

Electronic Information Engineering and computer Science (EIECS), 2021 international conference on

作者： Xiaonan Hu Weidong Wang Jingyu Li Baoguo Gao Hanzhi Li Research and Development Center Tianjin Richsoft Electric Power Information Technology Co. Ltd. Tianjin China

ISBN: (数字)9798331531409

ISBN: (纸本)9798331531416

As a cutting-edge development trend in the field of visualization, cloud rendering technology is currently dominated by game engine manufacturers. Cloud rendering technology based on WebGL engine has not yet been fully developed. This article conducts research on the method of three-dimensional real-time cloud rendering by developing cloud rendering through open-source WebGL engines, taking open-source component Cesium as the entry point. The aim is to solve the problem of high costs faced by small and micro enterprises when conducting secondary development and replacement of engines, thereby breaking through technical barriers and having independent ownership of core technology patents, and achieving a three-dimensional real-time cloud rendering technology application based on the Cesium engine.

关键词： visualization Patents Costs Three-dimensional displays Publishing Rendering (computer graphics) Cesium Servers Engines WebRTC

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A Survey on Automated CAD System of Liver Tumor using US Images 7

A Survey on Automated CAD System of Liver Tumor using US Ima...

引用

7th international conference on Communication and Electronics Systems, ICCES 2022

作者： Uplaonkar, Deepak S. Virupakshappa Rangayya Patil, Nagabhushan International Institute of Information Technology Department of Information Technology Pune India Sharnbasva University Department of Computer Science and Engineering Kalburagi India Sharnbasva University Department of Elctronics and Telecommunication Engineering Kalburagi India Poojya Doddappa Appa College of Engineering Department of Electrical and Elctronics Engineering Kalburagi India

ISBN: (数字)9781665496346

ISBN: (纸本)9781665496346

Visual analysis of human organs is currently one of the most active subjects under study in the field of computer vision. The ability of a machine to analyse human organs is a critical aspect in its development. Medical imaging is a procedure that allows clinicians to examine a part of the human body that is not naturally visible. In Medical Image Processing, analysis and visualization application allows for quantitative analysis and visualization of a variety of medical imaging modalities. The objective of this survey is to present an overview of current computer-assisted diagnosis approaches for detecting tumor lesions using ultrasound images. Research papers published between 2019 and 2021 from various standard databases were considered in preparation for the survey. The paper initially discusses the various speckle reduction approaches on ultrasound images, then various segmentation approaches based on level set are discussed. Finally various approaches for discrete wavelet transformation-based feature extraction and neural network-based classification are also discussed. The review gives an insight on the work carried out so far for reduction of speckle noise in ultrasound image, level set-based segmentation methods, discrete wavelet transformation-based feature extraction methods and artificial neural network based classification methods. © 2022 IEEE.

关键词： Surveys

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