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2019 Eurographics Workshop on Graphics and Cultural Heritage, GCH 2019

作者： Brenner, S. Sablatnig, R. TU Wien Institute of Visual Computing and Human-Centered Technology Austria

ISBN: (纸本)9783038680826

Multispectral imaging has become a popular tool to reveal properties and structures in cultural heritage objects that are hidden to the human observer. One of the inherent problems of multispectral imaging applications is chromatic aberration. Due to an extended spectral range, the effect appears more pronounced than in conventional photography in the visible spectrum. This paper is concerned with longitudinal chromatic aberrations, i.e. shifts of the focal plane along the principal axis of the camera, as they are hard to correct in post-processing and should be avoided during acquisition. To this end, a calibration scheme to measure the wavelength- and distance-dependent focal shift behavior of a given camera/lens system is proposed, which allows for a mechanical compensation at acquisition time. The approach is demonstrated on a multispectral imaging system for historical manuscript analysis. We show that the application of this compensation approach enables the acquisition of in-focus images in non-visible wavelengths using a lens optimized for the visible spectrum only. © 2019 Eurographics Association.

关键词： Aberrations

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"The support needs to be part of the system": designing inclusive eHealth applications for older adults with low eHealth literacy

"The support needs to be part of the system": designing incl...

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2022 Engaging Citizen Science Conference, CitSci 2022

作者： Prinzellner, Yvonne Simon, Ali Drachmann, Danielle Werner, Katharina Münter, Lars Bulsink, Vera Smits, Carolien Fitzpatrick, Geraldine Schwaninger, Isabel Johanniter Österreich Ausbildung und Forschung Gemeinnützige GmbH Ignaz-Köck-Straße 22 Vienna1210 Austria Danish Committee for Health Education Classensgade 71 5. Sal Copenhagen2100 Denmark TU Wien Institute of Visual Computing and Human-Centered Technology Human Computer Interaction Group Argentinierstraße 8 Vienna1040 Austria Roessingh Research and Development Roessinghsbleekweg 33b Enschede7522 Netherlands Arthur van Schendelstraat 600 Utrecht3511 MJ Netherlands

In the project "Got-IT", an online toolkit was developed to assist with the design of inclusive eHealth solutions targeting the promotion of healthy lifestyles among older adults (65+) with low eHealth literacy. The project consortium has used participatory citizen science as an approach to actively engage with the relevant stakeholders, including older adults with low eHealth literacy, eHealth developers, and secondary end users like eHealth professionals. We applied three different research designs, all centered on the active engagement of the different stakeholders, using the design of an eHealth app to ground the investigations. The outcomes of the Got-IT project align not only with the first objective of the AAL Programme ("better quality of life for older adults and their networks, by empowering the citizens to take care of their own health") but are also central components of citizen science as a whole, by actively engaging the different target groups at various levels of our research process. © Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0)

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Video shot analysis for digital curation and preservation of historical films

Video shot analysis for digital curation and preservation of...

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2019 Eurographics Workshop on Graphics and Cultural Heritage, GCH 2019

作者： Helm, D. Kampel, M. TU Wien Institute for Visual Computing and Human-Centered Technology Austria

ISBN: (纸本)9783038680826

In automatic video analysis and film preservation, Shot Boundary Detection (SBD) and Shot Type Classification (STC) are fundamental pre-processing steps. While previous research focuses on detecting and classifying shots in different video genres such as sports movies, documentaries or news clips only few studies investigate on SBD and STC in historical footage. In order to promote research on automatic video analysis the project visual History of the Holocaust (VHH) has been started in January 2019. The main aim of this paper is to present first results on the fundamental topics SBD and STC in the context of the project VHH. Therefore, a deep learning-based SBD approach is implemented to detect Abrupt Transitions (ATs). Furthermore, a CNN-based algorithm is analyzed and optimized in order to classify shots into the four categories: Extreme-Long-Shot (ELS), Long-Shot (LS), Medium-Shot (MS) and Close-Up (CU). Finally, both algorithms are evaluated on a self-generated historical dataset related to the National Socialism and the Holocaust. The outcome of this paper demonstrates a first quantitative evaluation of the SBD approach and displays a F1;Score of 0.866 without the need of any re-training or optimization. Moreover, the proposed STC algorithm reaches an accuracy of 0.71 on classifying shots. This paper contributes a significant base for future research on automatic shot analysis related to the project VHH. © 2019 Eurographics Association.

关键词： Deep learning

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Cost Volume Refinement for Depth Prediction

Cost Volume Refinement for Depth Prediction

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International Conference on Pattern Recognition

作者： João L. Cardoso Nuno Gonçalves Michael Wimmer Institute of Visual Computing and Human-Centered Technology TU Wien Vienna Austria Institute of Systems and Robotics University of Coimbra Portuguese Mint and Official Printing Office Lisbon

Light-field cameras are becoming more popular in the consumer market. Their data redundancy allows, in theory, to accurately refocus images after acquisition and to predict the depth of each point visible from the camera. Combined, these two features allow for the generation of full-focus images, which is impossible in traditional cameras. Multiple methods for depth prediction from light fields (or stereo) have been proposed over the years. A large subset of these methods relies on cost-volume estimates - 3D objects where each layer represents a heuristic of whether each point in the image is at a certain distance from the camera. Generally, this volume is used to regress a depth map, which is then refined for better results. In this paper, we argue that refining the cost volumes is superior to refining the depth maps in order to further increase the accuracy of depth predictions. We propose a set of cost-volume refinement algorithms and show their effectiveness.

关键词： Three-dimensional displays Smoothing methods Volume measurement Refining Redundancy Pipelines Cameras

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You get by with a little help:The effects of variable guidance degrees on performance and mental state

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visual Informatics 2019年第4期3卷 177-191页

作者： Davide Ceneda Theresia Gschwandtner Silvia Miksch TU Wien Faculty of InformaticsInstitute of Visual Computing&Human-Centered TechnologyFavoritenstrasse 9-11/193A-1040 ViennaAustria

Since it can be challenging for users to effectively utilize interactive visualizations,guidance is usually provided to assist users in solving *** is mentioned as an effective mean to overcome stall situations occurring during the ***,the effectiveness of a peculiar guidance solution usually varies for different analysis *** same guidance may have different effects on users with(1)different levels of *** choice of the appropriate(2)degree of guidance and the type of(3)task under consideration also affect the positive or negative outcome of providing *** these three factors,we conducted a user study to investigate the effectiveness of variable degrees of guidance with respect to the user’s previous knowledge in different analysis *** results shed light on the appropriateness of certain degrees of guidance in relation to different tasks,and the overall influence of guidance on the analysis outcome in terms of user’s mental state and analysis performance.

关键词： Guidance User study Knowledge Trust Mixed-initiative visual data analysis

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Shot Boundary Detection for Automatic Video Analysis of Historical Films 2nd

Shot Boundary Detection for Automatic Video Analysis of Hist...

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2nd International Workshop on Recent Advances in Digital Security: Biometrics and Forensics, BioFor 2019, 1st International Workshop on Pattern Recognition for Cultural Heritage, PatReCH 2019, 1st International Workshop eHealth in the Big Data and Deep Learning Era, e-BADLE 2019, International Workshop on Deep Understanding Shopper Behaviors and Interactions in Intelligent Retail Environments, DEEPRETAIL 2019 and Industrial session held at the 20th International Conference on Image Analysis and Processing, ICIAP 2019

作者： Helm, Daniel Kampel, Martin Institute of Visual Computing and Human-Centered Technology TU Wien Vienna Austria

ISBN: (纸本)9783030307530

In automatic video content analysis and film preservation, Shot Boundary Detection (SBD) is a fundamental pre-processing step. While previous research focuses on detecting Abrupt Transitions (AT) as well as Gradual Transitions (GT) in different video genres such as sports movies or news clips only few studies investigate in the detection of shot transitions in historical footage. The main aim of this paper is to create an SBD mechanism inspired by state-of-the-art algorithms which is applied and evaluated on a self-generated historical dataset as well as a publicly available dataset called Clipshots. Therefore, a three-stage pipeline is introduced consisting of a Candidate Frame Range Selection based on the network DeepSBD, Extraction of Convolutional Neural Network (CNN) Features and Similarity Calculation. A combination of pre-trained backbone CNNs such as ResNet, VGG19 and SqueezeNet with different similarity metrics like Cosine Similarity and Euclidean Distance are used and evaluated. The outcome of this paper displays that the proposed algorithm reaches promising results on detecting ATs in historical videos without the need of complex optimization and re-training processes. Furthermore, it points out the main challenges concerning historical footage such as damaged film reels, scratches or splices. The results of this paper contribute a significant base for future research on automatic video analysis of historical videos. © 2019, Springer Nature Switzerland AG.

关键词： Convolution

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INTERPRETABLE EMBEDDINGS FOR SEGMENTATION-FREE SINGLE-CELL ANALYSIS IN MULTIPLEX IMAGING

arXiv

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arXiv 2024年

作者： Gutwein, Simon Lazic, Daria Walter, Thomas Taschner-Mandl, Sabine Licandro, Roxane St. Anna Children’s Cancer Research Institute Vienna Austria TU Wien Institute of Visual Computing and Human-Centered Technology CVL Vienna Austria Medical University of Vienna Biomedical Imaging and Image-guided Therapy CIR Vienna Austria Mines Paris PSL University Paris75006 France Institut Curie ParisCedex 75248 France INSERM U900 ParisCedex 75248 France

Multiplex Imaging (MI) enables the simultaneous visualization of multiple biological markers in separate imaging channels at subcellular resolution, providing valuable insights into cell-type heterogeneity and spatial organization. However, current computational pipelines rely on cell segmentation algorithms, which require laborious fine-tuning and can introduce downstream errors due to inaccurate single-cell representations. We propose a segmentation-free deep learning approach that leverages grouped convolutions to learn interpretable embedded features from each imaging channel, enabling robust cell-type identification without manual feature selection. Validated on an Imaging Mass Cytometry dataset of 1.8 million cells from neuroblastoma patients, our method enables the accurate identification of known cell types, showcasing its scalability and suitability for high-dimensional MI data. © 2024, CC BY-NC-ND.

关键词： Feature Selection

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Acquisition evaluation on outdoor scanning for archaeological artifact digitalization 15

Acquisition evaluation on outdoor scanning for archaeologica...

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15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2020

作者： Kusuma Frisky, Aufaclav Zatu Fajri, Adieyatna Brenner, Simon Sablatnig, Robert Computer Vision Lab Institute of Visual Computing and Human-Centered Technology Faculty of Informatics TU Wien Wien Austria Department of Computer Science and Electronics Universitas Gadjah Mada Yogyakarta Indonesia Department of Archaeology Universitas Gadjah Mada Yogyakarta Indonesia

ISBN: (纸本)9789897584022

Archaeological archives are important assets because they provide primary information resources for research, mainly digital archives that not degraded. Instead of directly visiting a site, an archaeologist can examine and manipulate the data without harming the real object. However, choosing an efficient scanning scheme with detailed results is a challenging task. In this work, we present new sculpture models obtained in three different ways and assess it in two comparison approaches: A quantitative and qualitative assessment. The quantitative comparison architecture provides a detailed assessment of three different scanning mechanisms in two stages: point cloud and mesh comparison. This evaluation is purposed to describe the differences between unmodified data. Finally, a qualitative evaluation is performed by an expert and practitioner to explain the difference based on four different produced models to help their needs in the real application. Copyright © 2020 by SCITEPRESS – Science and technology Publications, Lda. All rights reserved.

关键词： Scanning

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Single-Modal Video Analysis of Personality Traits using Low-Level visual Features

Single-Modal Video Analysis of Personality Traits using Low-...

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Workshops on Image Processing Theory, Tools and Applications, IPTA

作者： Daniel Helm Martin Kampel Computer Vision Lab TU Wien Institute of Visual Computing Human-Centered Technology Vienna Austria

ISBN: (数字)9781728187501

ISBN: (纸本)9781728187518

The ability to analyze the first impression of a person automatically enables novel applications in human-computer interaction and other areas. A person's first impression can decide about a positive or negative outcome in different daily-life situations. The human brain is able to get a picture of the counterpart's personality at short notice. The main aim of this paper is to show how a system based on a standard Convolutional Neural Network (CNN) as well as a 3D-CNN architecture, can be built to solve a multi-label regression task using only visual low-level features. This paper investigates how various pre-processing methods, such as face-extraction and data-augmentation, influence the predicted personality confidences. Furthermore, it explores different training strategies and optimization techniques e.g. regularization in order to improve the model performance. The results of this paper demonstrate an image-based as well as a time-sequence-based system to predict the Big-Five personality dimensions of humans in short video sequences by solving a multi-label regression task. The approaches reach an overall accuracy of 0.891 by using visual features only.

关键词： Training visualization Image recognition Video sequences Computer architecture Pattern recognition Task analysis

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On Learning Vehicle Detection in Satellite Video

arXiv

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arXiv 2020年

作者： Pflugfelder, Roman Weissenfeld, Axel Wagner, Julian AIT Austrian Institute of Technology Center for Digital Safety & Security TU Wien Institute of Visual Computing & Human-Centered Technology

Vehicle detection in aerial and satellite images is still challenging due to their tiny appearance in pixels compared to the overall size of remote sensing imagery. Classical methods of object detection very often fail in this scenario due to violation of implicit assumptions made such as rich texture, small to moderate ratios between image size and object size. Satellite video is a very new modality which introduces temporal consistency as inductive bias. Approaches for vehicle detection in satellite video use either background subtraction, frame differencing or subspace methods showing moderate performance (0.26 - 0.82 F1 score). This work proposes to apply recent work on deep learning for wide-area motion imagery (WAMI) on satellite video. We show in a first approach comparable results (0.84 F1) on Planet’s SkySat-1 LasVegas video with room for further improvement. Copyright © 2020, The Authors. All rights reserved.

关键词： Textures

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