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31st International Conference on Multimedia Modeling, MMM 2025

作者： Stroh, Michael Kloda, Vojtěch Verner, Benjamin Vopálková, Zuzana Buchmüller, Raphael Jäckl, Bastian Hajko, Jakub Lokoč, Jakub Visual Computing Department of Computer Science Faculty of Natural Sciences Konstanz University Konstanz Germany SIRET Research Group Department of Software Engineering Faculty of Mathematics and Physics Charles University Prague Czech Republic Data Analysis and Visualization Department of Computer Science Faculty of Natural Sciences Konstanz University Konstanz Germany

ISBN: (纸本)9789819620739

We present a third version of the PraK system designed around an effective text-image and image-image search model. The system integrates sub-image search options for localized context search for CLIP and image color/texture and interfaces tailored to specific task types. A user study shows the benefits of sub-image search in homogeneous video collections. We further enhance the user experience of the PraK framework by re-designing the frontend and introducing task-specific views. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Video analysis

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PraK Tool: An Interactive Search Tool Based on Video Data Services 30th

PraK Tool: An Interactive Search Tool Based on Video Data S...

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30th International Conference on MultiMedia Modeling, MMM 2024

作者： Lokoč, Jakub Vopálková, Zuzana Stroh, Michael Buchmueller, Raphael Schlegel, Udo SIRET Research Group Department of Software Engineering Faculty of Mathematics and Physics Charles University Prague Czech Republic Visual Computing Department of Computer Science Faculty of Natural Sciences Konstanz University Konstanz Germany Data Analysis and Visualization Department of Computer Science Faculty of Natural Sciences Konstanz University Konstanz Germany

ISBN: (纸本)9783031533013

This paper presents a tool relying on data service architecture, where technical details of all VBS datasets are completely hidden behind an abstract stateless data layer. The data services allow independent development of interactive search interfaces and refinement techniques, which is demonstrated by a smart front-end component. The component supports common search features and allows users to exploit content-based statistics for effective filtering. We believe that video data services might be a valuable addition to the open-source VBS toolkit, especially when available for the competition on a shared server with all VBS datasets, extracted features, and meta-data behind. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Video recording

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Architecture proposal for adding FOG processing capability to a Smart Building Management System

Architecture proposal for adding FOG processing capability t...

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International Conference on Fog and Mobile Edge Computing (FMEC)

作者： David Martínez Casas Andrea Rey Presas José M. Cotos Yáñez José A. Taboada González Electronics and Computer Science Department Computer Graphics and Data Engineering (COGRADE) Research Group University of Santiago de Compostela Santiago de Compostela Spain

ISBN: (数字)9798350366488

ISBN: (纸本)9798350366495

This article examines the current state of the intelligent building monitoring system created for the University of Santiago de Compostela (USC) in the framework of the OPERE project and proposes a modification based on the Fog Computing paradigm. The study is developed in the context of the European regulations for the energy efficiency of facilities and the reduction of greenhouse gases. The current system implements the data processing in DADIS modules, developed by this research group for the acquisition and flexible transmission of information. These modules provide the information to the monitoring system which offers functionalities such as energy consumption dashboards, configurable operation schedules and ad hoc data visualization. However, the limitations of the current system include the difficulty in scaling the processing of the acquired information and database queries. The described upgrade proposes the extensive use of MQTT to standardize communications and allow the development of stand-alone applications to scale processing. The same architecture facilitates the incorporation of Big Data infrastructures that would solve even more complex query problems than those addressed in this scenario.

关键词： Schedules Smart buildings Multi-access edge computing Architecture Europe computer architecture Regulation Proposals Greenhouse gases Monitoring

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A proposal to measure the understanding of data visualization elements in visual analytics applications 10

A proposal to measure the understanding of data visualizatio...

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10th Learning Analytics Summer Institute Spain, LASI Spain 2022

作者： Vázquez-Ingelmo, Andrea García-Peñalvo, Francisco José Therón, Roberto Byrd, Vetria Camba, Jorge D. GRIAL Research Group University of Salamanca Paseo de Canalejas 169 Salamanca Spain VisUSAL Computer Science Department Universidad de Salamanca Salamanca Spain Computer Graphics Technology Purdue University West LafayetteIN United States

Data visualizations and information dashboards are useful but complex tools. They must be fully understood to draw proper insights and to avoid misleading conclusions. However, several elements and factors are involved in this domain, which makes it difficult to learn. In previous works, we proposed a meta-model to capture the primitive elements that compose visualizations and dashboards. This meta-model has served as a framework for conducting data visualization research, but also to develop a graphical tool for generating data visualizations and dashboards. This tool (namely MetaViz) enables users to create data visualizations through fine-grained components based on the entities represented in the meta-model. The main goal of the system is to provide a learning experience in which users can freely add and configure elements to understand how they influence the final display. This work describes work in progress to validate the pedagogical value of MetaViz in terms of the understanding of data visualization concepts. © 2022 Copyright for this paper by its authors.

关键词： Data visualization

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Building a dynamic opinion dashboard to categorize tweets for real-time sentiment analysis

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International Journal of Information Technology (Singapore) 2025年 1-7页

作者： Adekoya-Cole, Temitope Fernando, Sandra Maroju, Abhilash Samal, Chandra Kanta Aggarwal, Saurabh Brahma, Biswajit Assistive Technology Research Group SCDM London Metropolitan University London United Kingdom Department of Information Technology University of the Cumberlands Williamsburg United States Department of Computer Science Acharya Narendra Dev College Delhi University Delhi India San Jose State University San Jose United States Senior Data & Visualization Engineer McKesson Corporation 32559 Lake Bridgeport St Fremont United States

Twitter, a popular social media, and networking tool has evolved into an important source of real-time news and a hub for public opinions. Using Twitter data, the given paper investigates the possibility of applying sentiment analysis to identify tweets as positive, negative, or neutral and then presenting the results visually, resulting in an in-depth analysis of public opinion. To do this, a dynamic opinion dashboard is designed comprising three modules viz. the user interface built on HTML, the backend application running in Python and Twitter, and the data source. The dashboard is built on a Python Flask app that interacts with a Twitter API to collect tweets, a sentiment analysis library to classify the tweets, and a variety of visualization libraries to create charts and graphs. The proposed dashboard provides users with real-time insights from text data in a user-friendly way. The proposed work is validated and compared with existing studies as well as pre-trained sentiment analysis models based on evaluation metrics such as accuracy, precision, recall and F1 score. © Crown 2025.

关键词： Data visualization Dynamic dashboard Sentiment analysis TweetNLP

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Robust reconstruction of curved line structures in noisy point clouds

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Visual Informatics 2021年第3期5卷 1-14页

作者： Marcel Ritter Daniel Schiffner Matthias Harders Interactive Graphics and Simulation Group Department of Computer ScienceUniversity of InnsbruckAustria Airborne Hydromapping GmbH InnsbruckAustria DIPF|Leibniz Institute for Research and Information Education FrankfurtGermany

Point-based geometry representations have become widely used in numerous contexts,ranging from particle-based simulations,over stereo image matching,to depth sensing via light detection and *** application focus is on the reconstruction of curved line structures in noisy 3D point cloud *** algorithms operating on such point clouds often rely on the notion of a local *** the latter,our approach employs multi-scale neighborhoods,for which weighted covariance measures of local points are *** line structures are reconstructed via vector field tracing,using a bidirectional piecewise streamline *** also introduce an automatic selection of optimal starting points via multi-scale geometric *** pipeline development and choice of parameters was driven by an extensive,automated initial analysis process on over a million prototype test *** behavior of our approach is controlled by several parameters—the majority being set automatically,leaving only three to be controlled by a *** an extensive,automated final evaluation,we cover over one hundred thousand parameter sets,including 3D test geometries with varying curvature,sharp corners,intersections,data holes,and systematically applied varying types of ***,we analyzed different choices for the point of reference in the co-variance computation;using a weighted mean performed best in most *** addition,we compared our method to current,publicly available line reconstruction *** to thirty times faster execution times were achieved in some cases,at comparable error ***,we also demonstrate an exemplary application on four real-world 3D light detection and ranging datasets,extracting power line cables.

关键词： Computational geometry Noisy point clouds Line reconstruction Automatic Adaptive control

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Deterministic Ansätze for the Measurement-based Variational Quantum Eigensolver

arXiv

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arXiv 2023年

作者： Schroeder, Anna Heller, Matthias Gachechiladze, Mariami Merck KGaA Darmstadt Germany Department of Computer Science Technical University of Darmstadt Darmstadt Germany Fraunhofer Institute for Computer Graphics Research IGD Darmstadt Germany Interactive Graphics Systems Group Technical University of Darmstadt Darmstadt Germany

Measurement-based quantum computing (MBQC) is a promising approach to reducing circuit depth in noisy intermediate-scale quantum algorithms such as the Variational Quantum Eigensolver (VQE). Unlike gate-based computing, MBQC employs local measurements on a preprepared resource state, offering a trade-off between circuit depth and qubit count. Ensuring determinism is crucial to MBQC, particularly in the VQE context, as a lack of flow in measurement patterns leads to evaluating the cost function at irrelevant locations. This study introduces MBVQE-ansätze that respect determinism and resemble the widely used problem-agnostic hardware-efficient VQE ansatz. We evaluate our approach using ideal simulations on the Schwinger Hamiltonian and XY-model and perform experiments on IBM hardware with an adaptive measurement capability. In our use case, we find that ensuring determinism works better via postselection than by adaptive measurements at the expense of increased sampling cost. Additionally, we propose an efficient MBQC-inspired method to prepare the resource state, specifically the cluster state, on hardware with heavy-hex connectivity, requiring a single measurement round, and implement this scheme on quantum computers with 27 and 127 qubits. We observe notable improvements for larger cluster states, although direct gate-based implementation achieves higher fidelity for smaller instances. © 2023, CC BY.

关键词： Qubits

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Visual Analysis of Point Cloud Neighborhoods via Multi-Scale Geometric Measures

Visual Analysis of Point Cloud Neighborhoods via Multi-Scale...

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42nd Annual Conference on European Association for computer graphics, EUROgraphics 2021

作者： Ritter, M. Schiffner, D. Harders, M. Interactive Graphics and Simulation Group The Department of Computer Science University of Innsbruck Austria DIPF Leibniz Institute for Research and Information Education Frankfurt Germany Airborne Hydromapping GmbH Innsbruck Austria

ISBN: (纸本)9783038681335

Point sets are a widely used spatial data structure in computational and observational domains, e.g. in physics particle simulations, computer graphics or remote sensing. Algorithms typically operate in local neighborhoods of point sets, for computing physical states, surface reconstructions, etc. We present a visualization technique based on multi-scale geometric features of such point clouds. We explore properties of different choices on the underlying weighted co-variance neighborhood descriptor, illustrated on different point set geometries and for varying noise levels. The impact of different weighting functions and tensor centroids, as well as point set features and noise levels becomes visible in the rotation-invariant feature images. We compare to a curvature based scale space visualization method and, finally, show how features in real-world LiDAR data can be inspected by images created with our approach in an interactive tool. In contrast to the curvature based approach, with our method line structures are highlighted over growing scales, with clear border regions to planar or spherical geometric structures. © 2021 The Author(s).

关键词： Data visualization

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EFaR 2023: Efficient Face Recognition Competition

arXiv

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arXiv 2023年

作者： Kolf, Jan Niklas Boutros, Fadi Elliesen, Jurek Theuerkauf, Markus Damer, Naser Alansari, Mohamad Hay, Oussama Abdul Alansari, Sara Javed, Sajid Werghi, Naoufel Grm, Klemen Štruc, Vitomir Alonso-Fernandez, Fernando Diaz, Kevin Hernandez Bigun, Josef George, Anjith Ecabert, Christophe Shahreza, Hatef Otroshi Kotwal, Ketan Marcel, Sébastien Medvedev, Iurii Jin, Bo Nunes, Diogo Hassanpour, Ahmad Khatiwada, Pankaj Toor, Aafan Ahmad Yang, Bian Fraunhofer Institute for Computer Graphics Research IGD Germany TU Darmstadt Germany Department of Electrical and Computer Engineering Khalifa University Abu Dhabi United Arab Emirates Laboratory for Machine Intelligence Faculty of Electrical Engineering University of Ljubljana Slovenia Halmstad University Sweden Idiap Research Institute Martigny Switzerland Lausanne Switzerland Lausanne Switzerland Institute of Systems and Robotics University of Coimbra Coimbra Portugal eHealth and Welfare Security Group Department of Information Security and Communication Technology Norwegian University of Science and Technology Norway

This paper presents the summary of the Efficient Face Recognition Competition (EFaR) held at the 2023 International Joint Conference on Biometrics (IJCB 2023). The competition received 17 submissions from 6 different teams. To drive further development of efficient face recognition models, the submitted solutions are ranked based on a weighted score of the achieved verification accuracies on a diverse set of benchmarks, as well as the deployability given by the number of floating-point operations and model size. The evaluation of submissions is extended to bias, cross-quality, and large-scale recognition benchmarks. Overall, the paper gives an overview of the achieved performance values of the submitted solutions as well as a diverse set of baselines. The submitted solutions use small, efficient network architectures to reduce the computational cost, some solutions apply model quantization. An outlook on possible techniques that are underrepresented in current solutions is given as well. © 2023, CC BY-NC-SA.

关键词： Face recognition

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SynFacePAD 2023: Competition on Face Presentation Attack Detection Based on Privacy-aware Synthetic Training Data

arXiv

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arXiv 2023年

作者： Fang, Meiling Huber, Marco Fierrez, Julian Ramachandra, Raghavendra Damer, Naser Alkhaddour, Alhasan Kasantcev, Maksim Pryadchenko, Vasiliy Yang, Ziyuan Huangfu, Huijie Chen, Yingyu Zhang, Yi Pan, Yuchen Jiang, Junjun Liu, Xianming Sun, Xianyun Wang, Caiyong Liu, Xingyu Chang, Zhaohua Zhao, Guangzhe Tapia, Juan Gonzalez-Soler, Lazaro Aravena, Carlos Schulz, Daniel Fraunhofer Institute for Computer Graphics Research IGD Darmstadt Germany Department of Computer Science TU Darmstadt Darmstadt Germany Biometrics and Data Pattern Analytics Lab Universidad Autonoma de Madrid Spain Norway ID R&D Inc. New York United States School of Cyber Science and Engineering Sichuan University Chengdu China School of Computer Science and Technology Harbin Institute of Technology Harbin China School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture China Biometrics and Security Research Group Hochschule Darmstadt Darmstadt Germany I+D Vision Center Santiago Chile

This paper presents a summary of the Competition on Face Presentation Attack Detection Based on Privacy-aware Synthetic Training Data (SynFacePAD 2023) held at the 2023 International Joint Conference on Biometrics (IJCB 2023). The competition attracted a total of 8 participating teams with valid submissions from academia and industry. The competition aimed to motivate and attract solutions that target detecting face presentation attacks while considering synthetic-based training data motivated by privacy, legal and ethical concerns associated with personal data. To achieve that, the training data used by the participants was limited to synthetic data provided by the organizers. The submitted solutions presented innovations and novel approaches that led to outperforming the considered baseline in the investigated benchmarks. © 2023, CC BY-NC-SA.

关键词： Competition

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