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32nd International Conference in Central Europe on computer graphics, Visualization and computer Vision, WSCG 2024

作者： Komar, Alexander Riegler, Marco Preiner, Reinhold Augsdörfer, Ursula Institute of Computer Graphics and Knowledge Visualisation Graz University of Technology Austria

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 subdivision control polygon or control mesh respectively, from which the smooth subdivision limit surfaces can be derived. For the reconstruction of curves the system estimates the number and position of control points required to approximate the curve closely. To reconstruct subdivision surfaces from points, the system determines a sequence of CAD operations which is subject to mutation in the course of a genetic optimization. We discuss implementation details of the proposed genetic algorithms and demonstrate our approach on a number of example data. © 2024 University of West Bohemia. All rights reserved.

关键词： Mesh generation

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LatEd: A Geometric Latent Vector Editor 32

LatEd: A Geometric Latent Vector Editor

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32nd International Conference in Central Europe on computer graphics, Visualization and computer Vision, WSCG 2024

作者： Komar, Alexander Kammerer, Michael Khalilsaraei, Saeedeh Barzegar Augsdörfer, Ursula Institute of Computer Graphics and Knowledge Visualisation Graz University of Technology Austria

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 database. Two types of networks are evaluated in terms of lookup accuracy and reconstruction quality using a database of Lego pieces. Even with small training set a reasonable robustness to rotation and translation of the shapes was achieved. While a human can interpret uncompressed data just fine, the compressed values of the network might be cryptic and thus offer no insight regarding the uncompressed input. Therefore, we introduce a latent dimension editor which allows the user to examine the geometry content of the latent vector and its influence on the decoded shape. The latent vector editor enables the visual exploration of the latent vector, by making changes to the latent vector visible in real-time via a 3D visualization of the reconstructed object. © 2024 University of West Bohemia. All rights reserved.

关键词： Vectors

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Brain computer Interfacing with a Virtual Environment 32

Brain Computer Interfacing with a Virtual Environment

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32nd International Conference in Central Europe on computer graphics, Visualization and computer Vision, WSCG 2024

作者： Gamillscheg, Florian Ruprecht, Irena Settgast, Volker Pietroszek, Krzysztof Augsdörfer, Ursula Institute of Computer Graphics and Knowledge Visualisation Graz University of Technology Austria Fraunhofer Austria Graz Austria American University WashingtonDC United States Graz University of Technology Austria

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 (BCIs) have the potential to close this gap by enabling an immediate translation of human thoughts to commands that can be processed by a computer. This paper investigates the feasibility of employing an affordable commercial BCI device for VR interaction. In a preliminary study conducted in a Cave Automatic Virtual Environment (CAVE), we evaluate both the effectiveness and limitations of the popular BCI device Emotiv Insight. © 2024 University of West Bohemia. All rights reserved.

关键词： Virtual environments

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Visual Exploration of Cultural Heritage Collections with Linked Spatiotemporal, Shape and Metadata Views

Visual Exploration of Cultural Heritage Collections with Lin...

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2020 Vision, Modeling, and Visualization, VMV 2020

作者： Lengauer, S. Komar, A. Karl, S. Trinkl, E. Preiner, R. Schreck, T. Institute of Computer Graphics and Knowledge Visualisation Graz University of Technology Austria Institute of Classics University of Graz Austria

ISBN: (纸本)9783038681236

The analysis of Cultural Heritage (CH) artefacts is an important task in the Digital Humanities. Increasingly, rich CH artefact data comprising metadata of different modalities becomes available in digital libraries and research data repositories. However, the large amounts and heterogeneity of artefacts in these repositories compromise their accessibility for common domain analysis tasks, as domain researchers lack a structural overview of the spatial, temporal, and categorical traits of the artefacts in these collections. Still, researchers need to compare artefacts along different modalities, put them into context, and deal with possible uncertainties, subjectivities, or missing data. To date, many works support domain research via interactive visualisation. The majority relies primarily on visualisation of text and metadata including spatiotemporal, image and shape data. However, fewer consider these types of data in a tightly coupled way. We present an approach for tightly integrated multimodal visual exploration of large CH data collections along space, time and shape traits. Based on requirements obtained in collaboration with domain researchers, we introduce a set of interlinked views for exploration of said modalities. An appropriately defined approach automatically computes most significant correlations across different modalities, guiding the user towards detecting interesting artefact relationships. We apply our approach to pertinent archaeological data collections, and demonstrate that characteristic explorative tasks are effectively supported and domain-relevant artefact relations can be discovered. © 2020 The Author(s) Eurographics Proceedings © 2020 The Eurographics Association.

关键词： Metadata

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Sketch-aided retrieval of incomplete 3D cultural heritage objects 12

Sketch-aided retrieval of incomplete 3D cultural heritage ob...

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12th Eurographics Workshop on 3D Object Retrieval, 3DOR 2019, in conjunction with the 40th Annual Conference of the European Association for computer graphics, EG 2019

作者： Lengauer, S. Komar, A. Labrada, A. Karl, S. Trinkl, E. Preiner, R. Bustos, B. Schreck, T. Institute of Computer Graphics and Knowledge Visualisation Graz University of Technology Austria Institute of Archaeology University of Graz Austria Millenium Institute for Foundational Research on Data Department of Computer Science University of Chile Chile

ISBN: (纸本)9783038680772

Due to advances in digitization technology, documentation efforts and digital library systems, increasingly large collections of visual Cultural Heritage (CH) object data becomes available, offering rich opportunities for domain analysis, e.g., for comparing, tracing and studying objects created over time. In principle, existing shape- and image-based similarity search methods can aid such domain analysis tasks. However, in practice, visual object data are given in different modalities, including 2D, 3D, sketches or conventional drawings like profile sections or unwrappings. In addition, collections may be distributed across different publications and repositories, posing a challenge for implementing encompassing search and analysis systems. We introduce a methodology and system for cross-modal visual search in CH object data. Specifically, we propose a new query modality based on 3D views enhanced by user sketches (3D+sketch). This allows for adding new context to the search, which is useful e.g., for searching based on incomplete query objects, or for testing hypotheses on existence of certain shapes in a collection. We present an appropriately designed workflow for constructing query views from incomplete 3D objects enhanced by a user sketch based on shape completion and texture inpainting. Visual cues additionally help users compare retrieved objects with the query. We apply our method on a set of relevant 3D and view-based CH object data, demonstrating the feasibility of our approach and its potential to support analysis of domain experts in Archaeology and the field of CH in general. © 2019 The Author(s)

关键词： Textures

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Motif-Driven retrieval of greek painted pottery

Motif-Driven retrieval of greek painted pottery

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2019 Eurographics Workshop on graphics and Cultural Heritage, GCH 2019

ISBN: (纸本)9783038680826

The analysis of painted pottery is instrumental for understanding ancient Greek society and human behavior of past cultures in Archaeology. A key part of this analysis is the discovery of cross references to establish links and correspondences. However, due to the vast amount of documented images and 3D scans of pottery objects in today's domain repositories, manual search is very time consuming. computer aided retrieval methods are of increasing importance. Mostly, current retrieval systems for this kind of cultural heritage data only allow to search for pottery of similar vessel's shape. However, in many cases important similarity cues are given by motifs painted on these vessels. We present an interactive retrieval system that makes use of this information to allow for a motif-driven search in cultural heritage repositories. We address the problem of unsupervised motif extraction for preprocessing and the shape-based similarity search for Greek painted pottery. Our experimental evaluation on relevant repository data demonstrates effectiveness of our approach on examples of different motifs of interests. © 2019 Eurographics Association.

关键词： Behavioral research

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Interactive visual labelling versus active learning:an experimental comparison

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Frontiers of Information Technology & Electronic Engineering 2020年第4期21卷 524-535页

作者： Mohammad CHEGINI Jurgen BERNARD Jian CUI Fatemeh CHEGINI Alexei SOURIN Keith ANDREWS Tobias SCHRECK Institute of Computer Graphics and Knowledge Visualisation Graz University of TechnologyGraz 8010Austria School of Computer Science and Engineering Nanyang Technological UniversitySingapore 639798Singapore InfoVis Group University of British ColumbiaVancouver V6T1Z4Canada Max Planck Institute for Meteorology Hamburg 20146Germany Institute of Interactive Systems and Data Science Graz University of TechnologyGraz 8010Austria

Methods from supervised machine learning allow the classification of new data automatically and are tremendously helpful for data *** quality of supervised maching learning depends not only on the type of algorithm used,but also on the quality of the labelled dataset used to train the *** instances in a training dataset is often done manually relying on selections and annotations by expert analysts,and is often a tedious and time-consuming *** learning algorithms can automatically determine a subset of data instances for which labels would provide useful input to the learning *** visual labelling techniques are a promising alternative,providing effective visual overviews from which an analyst can simultaneously explore data records and select items to a *** putting the analyst in the loop,higher accuracy can be achieved in the resulting *** initial results of interactive visual labelling techniques are promising in the sense that user labelling can improve supervised learning,many aspects of these techniques are still largely *** paper presents a study conducted using the mVis tool to compare three interactive visualisations,similarity map,scatterplot matrix(SPLOM),and parallel coordinates,with each other and with active learning for the purpose of labelling a multivariate *** results show that all three interactive visual labelling techniques surpass active learning algorithms in terms of classifier accuracy,and that users subjectively prefer the similarity map over SPLOM and parallel coordinates for *** also employ different labelling strategies depending on the visualisation used.

关键词： Interactive visual labelling Active learning Visual analytics

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Immersive Analytics of Anomalies in Multivariate Time Series Data with Proxy Interaction

Immersive Analytics of Anomalies in Multivariate Time Series...

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International Conference on Cyberworlds

作者： Simon Kloiber Josef Suschnigg Volker Settgast Christoph Schinko Martin Weinzerl Tobias Schreck Reinhold Preiner Institute of Computer Graphics and Knowledge Visualisation Graz University of Technology Austria Pro2Future GmbH Austria Fraunhofer Austria Research GmbH Austria AVL List GmbH Austria

ISBN: (数字)9781728164977

ISBN: (纸本)9781728164984

In industry and science, sensor data play a vital role in research, optimisation, monitoring, testing and many other use cases. When performing tests with repeated cycles of similar behaviour, e.g., durability tests, it is often important to find anomalous sensor behaviour that deviates from regular patterns in the data. We here explore the design space of VRbased immersive analytics for time series data, for use e.g., in engineering contexts where an underlying application is also given in VR. The use of 3D visualisation for time series exploration is a much-discussed topic and careful consideration for its use must be taken. With the rise of immersive environments, we re-visit the classic problem of 3D time series visualisation and introduce an immersive walk-up usable interaction proxy that supports efficient navigation of otherwise possibly occluded time series views. The proxy indicates anomalies in the data for easy access and provides efficient zooming and filtering controls, among other effective interaction possibilities. This approach is combined with suitable data analysis techniques, providing an environment for effective and efficient immersive anomaly detection and comparative data analysis that we call WaveCharts. We demonstrate the applicability of our approach by two real-world use cases, and we discuss the necessary tools it provides to aid the analysis process of large sensor data.

关键词： Three-dimensional displays Data analysis Time series analysis Data visualization Tools Space exploration Testing

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Interaction concepts for collaborative visual analysis of scatterplots on large vertically-mounted high-resolution multi-touch displays 10

Interaction concepts for collaborative visual analysis of sc...

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10th Forum Media Technology, FMT 2017 and 3rd All Around Audio Symposium

作者： Chegini, Mohammad Shao, Lin Lehmann, Dirk J. Andrews, Keith Schreck, Tobias Institute of Computer Graphics and Knowledge Visualisation Graz University of Technology Austria University of Magdeburg Germany Institute of Interactive Systems and Data Science Graz University of Technology Austria

Large vertically-mounted high-resolution multitouch displays are becoming increasingly available for interactive data visualisation. Such devices are well-suited to small-team collaborative visual analysis. In particular, the visual analysis of large high-dimensional datasets can benefit from high-resolution displays capable of showing multiple coordinated views. This paper identifies some of the advantages of using large, high-resolution displays for visual analytics in general, and introduces a set of interactions to explore high-dimensional datasets on large vertically-mounted high-resolution multi-touch displays using scatterplots. A set of touch interactions for collaborative visual analysis of scatterplots have been implemented and are presented. Finally, three perception-based level of detail techniques are introduced for such displays as a concept for further implementation.

关键词： Data visualization

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