WSCG 2024: Full Papers Proceedings Domovská stránka kolekce Zobrazit statistiky
Aguirre-López, Mario A.
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Izaguirre-Prado, Omar Efraín
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Soto-Villalobos, Roberto
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Hueyotl-Zahuantitla, Filiberto
A Novel Silhouette Extraction Method for Binary Images Based on the Wall-Follower Algorithm Silhouette extraction involves separating objects of interest from their background, which has several applications in image processing. Among the silhouette extraction techniques, contour tracing is commonly applied to images with a uniform background. This paper introduces a novel contribution to... |
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Freire, Pedro da Silva
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Pereira, João Madeiras
Dynamic Many-Light Importance Sampling for Real-Time Ray Tracing One of the main performance-heavy areas in raytracing is light sampling. Light sampling is solved in a process called next-event estimation(NEE), where light samples are taken at each ray intersection. Since real-time rendering is an objective, instead of sampling all the luminaries, ju... |
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Mrzyglod, Jan
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Kowalski, Przemysław
The color recognition methods for the active markers in the motion capture system, using various techniques, including ML The article focuses on a method for reliably identify moving colored artificial markers in real-time. The marker was used to determine the 3D position in the space of the user(s). The goal was to ensure that points were found and identified predictably and reliably by... |
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Drofova, Irena
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Adámek, Milan
Analysis of natural lighting conditions for the digitization of artwork in an art gallery interior The paper discusses the analysis of natural lighting conditions for digitizing art. The emphasis is on a realistic 3D digital reproduction of a work of art in natural lighting conditions in the interior of an art gallery. The art object is scanned and digitized in&... |
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Ben Amar, Hassene
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Okubo, Masashi
Study of Evolution in Virtual Worlds This paper investigates the evolution of agents within a virtual world, focusing on DNA transfer between gener ations, identification of significant genes and the explorations of parameters influencing survival and gene signif icance. To address these questions, we create an artificial life&... |
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Buric, Matija
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Ivasic-Kos, Marina
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Martincic-Ipsic, Sanda
The Disease of the Canine Eye - From Image to Diagnosis Using AI This research examines the application of computer vision (CV) and large language models (LLM) in diagnosing eye diseases in dogs. The study utilizes a U-Net framework, incorporating convolutional neural networks (CNNs) such as ResNet, Inception, VGG, and EfficientNet, to enhance the s... |
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Lee, Yuan-Kang
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Ding, Jian-Jiun
Sharpness Measurement by Edge-related Frequency Components In this paper, a novel no-reference image quality metric of sharpness is proposed. Our image quality metric is evaluated on two key attributes discerned during the assessment of image sharpness by the human visual system (HVS): 1. Image sharpness is principally contin... |
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Alwuqaysi, Bdour
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Abdul-Rahman, Alfie
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Borgo, Rita
Correlational Data Visualizations with Colored Bar Charts \ |
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Frasiolas, Panagiotis
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Reppas, Asterios
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Konstantoudakis, Konstantinos
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Zarpalos, Dimitrios
Lightweight single image dehazing utilizing relative depth information Considering the need for lightweight and fast implementations, this paper presents an architecture based on a Mo bileVit encoder for efficiency and speed, introducing a fully convolutional lightweight decoder with skip connec tions for feature extraction. The main purpose of this network... |
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Tamin, Owen
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Karim, Samsul Ariffin Abdul
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Hasan, Mohammad Khatim
A Comparative Study of Convex Combination and Inner Ordinate Methods For Scattered Data Interpolation Using Quartic Triangular Patch In this study, we perform a comparative evaluation and assessment for the scattered data interpolation using a quartic polynomial triangular patch with ten control points on a triangular domain. The comparison is made using two different convex combinations and inner ordinates methods, ... |
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Gamillscheg, Florian
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Ruprecht, Irena
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Settgast, Volker
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Pietroszek, Krzysztof
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Augsdoerfer, Ursula
Brain Computer Interfacing with a Virtual Environment Virtual Reality (VR) applications constantly strive for more realism, immersion and intuitive user experiences. Traditional VR controllers can hinder full immersion, since they form an additional barrier between the user’s thoughts or intentions and the virtual world. Brain computer interfaces (B... |
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Komar, Alexander
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Kammerer, Michael
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Barzegar Khalilsaraei, Saeedeh
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Augsdoerfer, Ursula
LatEd: A Geometric Latent Vector Editor Using a neural network approach, a shape may be compressed to a one-dimensional vector, the so-called latent dimension or latent vector. This latent shape dimension is examined in this paper. This latent vector of a shape is used to identify the corresponding shape in a d... |
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Komar, Alexander
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Riegler, Marco
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Preiner, Reinhold
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Augsdoerfer, Ursula
Genetic Subdivision Curve and Surface Reconstruction In this paper we employ a new genetic algorithm approach for CAD shape reconstruction, where a mathematical shape representation is reconstructed from point data. We reconstruct planar subdivision curves and 3D subdivision meshes from ordered input point data by fitting the corresponding... |
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Wu, FuChe
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Chen, Wei-Cheng
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Dellinger, Andrew
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Cheng, Han-Wen
Real-Size Experience for Virtual Try-On |
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Heinemann, Mika Benjamin
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Kernbauer, Thomas
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Fleck, Philipp
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Arth, Clemens
Spotlight Control for Real-Time Targeting Off-road heavy machinery such as snow groomers or excavators, often operate in low-light and hazardous envi ronments. In this work, we explore the development of an intelligent camera-spotlight system with automatic and manual control to illuminate points of interest, such as obstacles ... |
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Evain, Alexandre
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Khemmar, Redouane
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Orzalesi, Mathieu
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Ahmedali, Sofiane
Impact of Calibration Matrices on 3D Monocular Object Detection: Filtering, Dataset Combination and Integration of Synthetic Data This research is funded and supported by SEGULA Technologies. We would like to thank SEGULA Tech nologies for their collaboration and for allowing us to conduct this research. We would like to thank also the engineers of the Autonomous Navigation Laboratory (ANL) of IRSEEM for... |
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Niewiadomska-Kaplar, Justyna
Polychromatism of all light waves and a new approach to the interpretation of fluorescence mechanisms; Idea of the fluorescent color monitor In scientific literature it is considered that only white light is polychromatic and that it is composed of countless monochromatic waves. This research on light vision mechanisms in biosystems and on the mechanisms of formation of deficits in color discrimination reveals that... |
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Eilermann, Sebastian
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Petroll, Christoph
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Hoefer, Philipp
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Niggemann, Oliver
3D Multi-Criteria Design Generation and Optimization of an Engine Mount for an Unmanned Air Vehicle Using a Conditional Variational Autoencoder One of the most promising developments in computer vision in recent years is the use of generative neural net works for functionality condition-based 3D design reconstruction and generation. Here, neural networks learn dependencies between functionalities and a geometry in a very effective... |
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Qadri, Juwaria
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Jothi, J. Angel Arul
ECNNXAI: Ensembled CNNs with eXplainable Artificial Intelligence for Colon Histopathology Image Classification Colon cancer is ranked as the third most commonly diagnosed cancer and second for causing the most cancer related deaths. Histopathology is a crucial diagnostic tool for cancer since it enables the microscopic analysis of tissue samples to pinpoint abnormal cells, to identif... |
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Bartolovic, Eduard
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Höfer, Tobias
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Hage, Clemens
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Nischwitz, Alfred
From Sources to Solutions: Enhancing Object Detection Models through Synthetic Data Object detection, a fundamental task in computer vision, plays a crucial role in various applications such as au tonomous driving, surveillance, and robotics. However, training models for this task require vast amounts of high-quality data, often involving labor-intensive manual labeling. Synthet... |
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