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

共 12023 条记录，以下是131-140 订阅

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Wireless Electromagnetic Tracking System for Wireless Capsule Endoscope

Wireless Electromagnetic Tracking System for Wireless Capsul...

引用

IEEE MTT-S international Microwave Bio conference ((IMBIOC)

作者： Xiaoyang Wu Yuming Fu Yong-Xin Guo Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore Department of Electrical Engineering City University of Hong Kong Hong Kong China

ISBN: (数字)9798331510473

ISBN: (纸本)9798331510480

Electromagnetic tracking (EMT) is widely used in image-guided surgical procedures, enabling precise tracking of the position and orientation of medical instruments. However, the traditional wired EMT system needs wires to be led out from the transmitting side to the receiving side, rendering it unsuitable for tracking in vivo biomedical implants. This study proposes a 6-DoF wireless tracking hybrid method based on the EMT and inertial measurement unit.

关键词： Wireless communication Microwave measurement Measurement units Wires Surgery Inertial navigation Rendering (computer graphics) Microwave theory and techniques Electromagnetics Microwave imaging

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A Comparative Analysis of Multi-Modal Medical Image Fusion Techniques using MSVD, WPD, PCA, and DWT

A Comparative Analysis of Multi-Modal Medical Image Fusion T...

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Cognitive Computing in Engineering, Communications, Sciences and Biomedical Health Informatics (IC3ECSBHI), international conference on

作者： Shailesh Bhosekar Prabhishek Singh Deepak Garg School of Computer Science and Artificial Intelligence SR University Warangal Telangana India School of Computer Science Engineering and Technology Bennett University Greater Noida India

ISBN: (数字)9798331518523

ISBN: (纸本)9798331518530

Image fusion is a technique used in image processing to create a more comprehensive representation by combining features and data from several images. Incorporating medical images from several imaging modalities, such as computed tomography (CT) scans, Positron Emission Tomography (PET) and magnetic resonance imaging (MRI), into a single set of data is what multi-modal medical image fusion is all about. Better visualization of anatomical structures and clinical conditions is the outcome of this integration, which increases diagnostic accuracy by using the strengths of each modality. In this paper, MRI, CT, and PET scans are used as experimental modalities. This review aims to compare various multi modal medical image approach based on Multi-resolution Singular Value Decomposition (MSVD), Principal Component Analysis (PCA), Discrete Wavelet Transform (DWT), and Wavelet Packet Decomposition (WPD). This paper focuses on exploring latest conventional and non-conventional research being done using these domains. It also compares these methods based on various image quality parameters, and various quantitative checks. Based on this comparison, PCA shows the best results in the comparison as the overall visual and parametric quality of fusion results are better than compared methods.

关键词： visualization Magnetic resonance imaging Computed tomography Wavelet analysis Wavelet packets Discrete wavelet transforms Positron emission tomography Medical diagnostic imaging Image fusion Principal component analysis

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Efficient Multi-Bounce Ray Tracing for Specular and Transparent Materials in NeRF

Efficient Multi-Bounce Ray Tracing for Specular and Transpar...

引用

IEEE international conference on Artificial Intelligence and Virtual Reality (AIVR)

作者： Haozhe Liu Yu Wei Tan Anand Bhojan School of Computing National University of Singapore

ISBN: (数字)9798331521578

ISBN: (纸本)9798331521585

With advancements in 3D reconstruction and computer graphics, Neural Radiance Fields (NeRF) has emerged as a powerful technique in novel view synthesis, holding potential for immersive extended reality (XR) and gaming applications. However, NeRF relies on volume rendering which cannot handle view-dependent light interactions like refraction and reflection well, which are crucial for realistic rendering in these areas. NeRF's hash encoding method also has high memory demands, limiting its utility for real-world scenes. We introduce a two-phase approach that improves NeRF's applicability for 3D environments. First, using object masks, we employ FlexiCubes to reconstruct specular and transparent objects with fewer polygons and model a neural field to capture refraction and reflection effects. Second, we propose a new frequency encoding filter that enhances visual quality while using just 10% of the memory required by hash encoding, enabling a multi-bounce ray-tracing module for reflection and refraction. Our method advances the integration of NeRF into realistic and memory-efficient frameworks suitable for XR and gaming experiences.

关键词： Solid modeling visualization Three-dimensional displays Memory management Ray tracing Neural radiance field Rendering (computer graphics) Encoding Reflection Optimization

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Faster Algorithms for Grid and Layered Drawings of Plane 3-Trees 17th

Faster Algorithms for Grid and Layered Drawings of Plane ...

引用

17th international conference on Combinatorial Optimization and Applications, COCOA 2024

作者： Hossain, Ahmed Islam, Md. Hasanul Mondal, Debajyoti Rahman, Md. Saidur Graph Drawing and Information Visualization Laboratory Department of Computer Science and Engineering (CSE) Bangladesh University of Engineering and Technology (BUET) Dhaka Bangladesh Department of Computer Science University of Saskatchewan Saskatoon Canada

ISBN: (纸本)9789819644445

A grid drawing of a plane graph G is a planar drawing of G such that each vertex is mapped to an integer grid point and each edge is mapped to a straight line segment with the endpoints determined by its end vertices. The area of a grid drawing is the area of the smallest axis-aligned rectangle that encloses the drawing. A k-layer drawing of G is a planar drawing on a set L of k horizontal lines such that each vertex is mapped to a point on L and each edge is mapped to a straight line segment. A minimum area (minimum-layer) drawing of G is a straight-line grid (layered) drawing of G where the area (number of layers) is minimized. In this paper we examine the grid and layered drawing of a well-studied class of planar graphs called plane 3-tree. Given a n-vertex plane 3-tree, one can compute a straight line drawing with minimum number of layers or area in O(n⁵) and O(n⁹logn) time, respectively [Mondal et al., JGAA, 15(2), 2011]. Here we improve the running times to O(n³) and O(n⁷logn), respectively. We then give a fast approximation algorithm for computing minimum-layer drawings for a nontrivial subclass of plane 3-trees. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Drawing (graphics)

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Proceedings of the 12th IASTED international conference on computer graphics and imaging, CGIM 2011

Proceedings of the 12th IASTED International Conference on C...

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12th IASTED international conference on computer graphics and imaging, CGIM 2011

ISBN: (纸本)9780889868656

The proceedings contain 17 papers. The topics discussed include: adaptive moving least squares for smoothing point clouds;figure out perspectives: perceptually realistic avatar visualization;X-Phong: extended phong lighting model for illustrative visualization;a fast knowledge-based plane reconstruction method from noisy 3D point cloud data;an efficient parallel thinning algorithm using one and two sub-iterations;multiresolution terrain generation based on implicit restricted quadtree;online authoring for augmented reality remote maintenance;realtime color adjustment for color-vision impaired users;simulation of autonomous agents using terrain reasoning;a geometric approach to improve performance of a collision detection algorithm derived from GJK and LC algorithms;and level-of-detail for time-varying surfaces on the GPU.

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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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international Joint conference on computer Vision, imaging and computer graphics Theory and Applications, VISIGRAPP 2014

International Joint Conference on Computer Vision, Imaging a...

引用

international Joint conference on computer Vision, imaging and computer graphics – Theory and Applications, VISIGRAPP 2014

ISBN: (纸本)9783319251165

The proceedings contain 19 papers. The special focus in this conference is on computer graphics Theory and Applications. The topics include: Past, present, and future of and in software visualization;distribution interpolation of the radon transforms for shape transformation of gray-scale images and volumes;multistory floor plan generation and room labeling of building interiors from laser range data;semantic composition of language-integrated shaders;simulated virtual crowds coupled with camera-tracked humans;multi-kernel ray traversal for graphics processing units;user’s interpretations of features in visualization;a fractal approach to hierarchy visualization;a potential field function for overlapping point set and graph cluster visualization;designing close and distant reading visualizations for text re-use;age estimation using 3D shape of the face;coupling dynamic equations and satellite images for modelling ocean surface circulation;affine coordinate-based parametrized active contours for 2D and 3D image segmentation;extended bayesian helmholtz stereopsis for enhanced geometric reconstruction of complex objects;efficient region-based classification for whole slide images;unsupervised visual hull reconstruction of a dense dataset;rock fragment boundary detection using compressed random features and retargeting framework based on monte-carlo sampling.

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Exploring Machine Learning and Deep Learning for Brain Tumor Detection: A Review

Exploring Machine Learning and Deep Learning for Brain Tumor...

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2025 international conference on Visual Analytics and Data visualization, ICVADV 2025

作者： Vishwakarma, Uma Yadav, Pritaj Jain, Anurag Rabindranath Tagore University Department of Computer Science & Engineering M.P. Bhopal India

ISBN: (纸本)9798331521394

Brain tumor detection has emerged as a critical field of research, given the increasing incidence of tumors and their impact on patients' lives. Recent advancements in machine learning (ML) and deep learning (DL) have revolutionized medical imaging, offering enhanced accuracy and efficiency in diagnosing brain tumors. This review comprehensively explores various ML and DL techniques employed for brain tumor detection, with a focus on supervised and unsupervised learning methods. Key algorithms such as convolutional neural networks (CNNs), random forests, and support vector machines (SVMs) are evaluated in terms of their classification performance, segmentation capabilities, and diagnostic accuracy. Moreover, the paper highlights the role of pre-processing methods, feature extraction techniques, and the challenges of imbalanced datasets in achieving robust models. © 2025 IEEE.

关键词： Convolutional neural networks

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A Novel Sky-Aware Dehazing Approach for Outdoor Autonomous Systems

A Novel Sky-Aware Dehazing Approach for Outdoor Autonomous S...

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Software Engineering and computer Science (CSECS), international conference on

作者： Xiaoyan Wu Dali Xu Fangfa Fu Bing Yang Hongyang Liu Kanglong Liu Xiyu Ding Chao Wu Na Niu School of Computer and Control Engineering Northeast Forestry University Harbin China School of Astronautics Harbin Institute of Technology Harbin China School of Computer Science Harbin University of Science and Technology Harbin China

ISBN: (数字)9798331522216

ISBN: (纸本)9798331522223

Clear outdoor images are essential for autonomous driving and accurate target detection, especially in haze. The majority of algorithms are unable to adequately address the issue of dehazing, resulting in a range of distortions, particularly in the sky area. This paper proposes an advanced dehazing algorithm for enhancing sky-area visuals (ESV). We segment the image into sky and non-sky areas, with atmospheric light levels being determined within the sky area. To enhance the recovery of the sky region, we suggest fine-tuning the sky's transmission to a predetermined constant value. Ultimately, the dehazed image is retrieved utilizing the atmospheric scattering model. Extensive experiments have shown that our proposed algorithm outperforms alternative methods, increasing PSNR by up to 1.3733%, 1.6360%, 2.4169%, 0.9512%, SSIM by up to 4.8995%, 0.6281%, 6.5335%, 8.7165%, enhancing the visuals of sky-area, compared to DCP, CAP, HC-CEP and AOD-Net.

关键词： visualization Atmospheric modeling Software algorithms Scattering Reinforcement learning Object detection Distortion Rendering (computer graphics) Robustness Software engineering

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Comparative Assessment of Modern Approaches for 3D Reconstruction

Comparative Assessment of Modern Approaches for 3D Reconstru...

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international conference on Radioelektronika

作者： Oleh Kryvoshei Patrik Kamencay Roberta Hlavata Adam Stech Miroslav Benco Department of Multimedia and Information-Communication Technologies University of Zilina Zilina Slovakia

ISBN: (数字)9798331544478

ISBN: (纸本)9798331544485

This paper explores and evaluates the strengths and weaknesses of neural and Gaussian-based approaches in 3D reconstruction. While neural radiance fields (NRFs) methods are increasingly favored for their adaptability and excellent outcomes, Gaussian techniques stand out for their analytical efficiency and robustness. This study systematically evaluates these both paradigms by comparing their performance in terms of accuracy, computational complexity, scalability, and real-world feasibility. In this paper, we analyze their effectiveness in reconstructing diverse 3D environments, considering factors such as noise resilience, data requirements, and rendering quality. Through experimental comparisons and benchmarking against standard datasets, our aim is to identify the strengths and limitations of each method and determine their suitability for specific applications in computer vision and graphics. By offering insights into the trade-offs between neural and Gaussian-based approaches, this paper contributes to the ongoing development of efficient and high-fidelity 3D reconstruction techniques. The findings will aid researchers and practitioners in selecting appropriate methods for different use cases, ultimately advancing the state of the art in 3D vision and computational graphics. Furthermore, the paper highlights the potential integration of NeRF in medical imaging, where it offers significant promise for generating 3D reconstructions from standard 2D medical scans. These reconstructions could revolutionize diagnostic accuracy, enhance surgical planning, and improve medical education.

关键词： Three-dimensional displays Accuracy Neural networks Surgery Neural radiance field Rendering (computer graphics) Real-time systems Planning Image reconstruction Standards

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