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SSRN 2018年

作者： Zheng, Jianxing Zhang, Bofeng Yue, Xiaodong Zou, Guobing Ma, Jianhua Jiang, Keyuan School of Computer Engineering and Science Shanghai University Shanghai200444 China Faculty of Computer and Information Sciences Hosei University Japan Department of Computer Information Technology & Graphics Purdue University CalumetIN United States

In the micro-blog scenario, personal user profiling relying on content is limited for recommending desired diverse subjects due to its shortcomings of short text, often leading to a poor recall. Currently, many methods only utilized the personal knowledge from each individual user to represent user profile without considering the neighborhood information. However, resource information related to neighboring friends play an important role in improving the performance of recommender systems. In this paper, we present the personalized expanded user profiling for micro-blog subject recommendation via ontology semantics structure. Next, taking into account diffusion ability of followee friends, we discuss resource perception relationship (RPR) and follow perception relationship (FPR). Finally, we discuss how, by adjusting the importance of RPR and FPR, the neighborhood is selected to construct neighborhood-user profile, which can mine new relevant subjects for target user. Our experimental results demonstrate the effectiveness of our neighborhood-user profiling in comparison to the existing collaborative filtering and personal user profile recommendation approaches on Sina micro-blog platform datasets. © 2018, The Authors. All rights reserved.

关键词： User profile

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VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images

arXiv

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arXiv 2020年

作者： Sekuboyina, Anjany Kumar Husseini, Malek E. Bayat, Amirhossein Löffler, Maximilian Liebl, Hans Li, Hongwei Tetteh, Giles Kukačka, Jan Payer, Christian Štern, Darko Urschler, Martin Chen, Maodong Cheng, Dalong Lessmann, Nikolas Hu, Yujin Wang, Tianfu Yang, Dong Xu, Daguang Ambellan, Felix Amiranashvili, Tamaz Ehlke, Moritz Lamecker, Hans Lehnert, Sebastian Lirio, Marilia de Olaguer, Nicolás Pérez Ramm, Heiko Sahu, Manish Tack, Alexander Zachow, Stefan Jiang, Tao Ma, Xinjun Angerman, Christoph Wang, Xin Brown, Kevin Kirszenberg, Alexandre Puybareau, Élodie Chen, Di Bai, Yiwei Rapazzo, Brandon H. Yeah, Timyoas Zhang, Amber Xu, Shangliang Hou, Feng He, Zhiqiang Zeng, Chan Xiangshang, Zheng Liming, Xu Netherton, Tucker J. Mumme, Raymond P. Court, Laurence E. Huang, Zixun He, Chenhang Wang, Li-Wen Ling, Sai Ho Huynh, Lê Duy Boutry, Nicolas Jakubicek, Roman Chmelik, Jiri Mulay, Supriti Sivaprakasam, Mohanasankar Paetzold, Johannes C. Shit, Suprosanna Ezhov, Ivan Wiestler, Benedikt Glocker, Ben Valentinitsch, Alexander Rempfler, Markus Menze, Björn H. Kirschke, Jan S. Department of Informatics Technical University of Munich Germany Munich School of BioEngineering Technical University of Munich Germany Department of Neuroradiology Klinikum Rechts der Isar Germany Department for Quantitative Biomedicine University of Zurich Switzerland Friedrich Miescher Institute for Biomedical Engineering Switzerland Institute of Biological and Medical Imaging Helmholtz Zentrum München Germany Department of Computing Imperial College London United Kingdom Institute of Computer Graphics and Vision Graz University of Technology Austria Gottfried Schatz Research Center: Biophysics Medical University of Graz Austria School of Computer Science The University of Auckland New Zealand Computer Vision Group iFLYTEK Research South China China Department of Radiology and Nuclear Medicine Radboud University Medical Center Nijmegen Netherlands Shenzhen Research Institute of Big Data China School of Biomedical Engineering Health Science Center Shenzhen University China NVIDIA Corporation United States Zuse Institute Berlin Germany 1000shapes GmbH Berlin Germany Damo Academy Alibaba Group China Department of Mathematics University of Innsbruck Austria Department of Electronic Engineering Fudan University China New York University United States France Deep Reasoning AI Inc United States Technical University of Munich Germany East China Normal University China Chinese Academy of Sciences China Lenovo Group China Ping An Technologies China College of Computer Science and Technology Zhejiang University China Real Doctor AI Research Centre Zhejiang University China The University of Texas MD Anderson Cancer Center United States Department of Electronic and Information Engineering The Hong Kong Polytechnic University China Department of Computing The Hong Kong Polytechnic University China The School of Biomedical Engineering University of Technology Sydney Australia Department of Biomedical Engineering Brno University of Technology Czech Republic India

Vertebral labelling and segmentation are two fundamental tasks in an automated spine processing pipeline. Reliable and accurate processing of spine images is expected to benefit clinical decision support systems for diagnosis, surgery planning, and population-based analysis of spine and bone health. However, designing automated algorithms for spine processing is challenging predominantly due to considerable variations in anatomy and acquisition protocols and due to a severe shortage of publicly available data. Addressing these limitations, the Large Scale Vertebrae Segmentation Challenge (VerSe) was organised in conjunction with the International Conference on Medical Image Computing and computer Assisted Intervention (MICCAI) in 2019 and 2020, with a call for algorithms tackling the labelling and segmentation of vertebrae. Two datasets containing a total of 374 multi-detector CT scans from 355 patients were prepared and 4505 vertebrae have individually been annotated at voxel level by a human-machine hybrid algorithm (https://***/nqjyw/, https://***/t98fz/). A total of 25 algorithms were benchmarked on these datasets. In this work, we present the results of this evaluation and further investigate the performance variation at the vertebra level, scan level, and different fields of view. We also evaluate the generalisability of the approaches to an implicit domain shift in data by evaluating the top-performing algorithms of one challenge iteration on data from the other iteration. The principal takeaway from VerSe: the performance of an algorithm in labelling and segmenting a spine scan hinges on its ability to correctly identify vertebrae in cases of rare anatomical variations. The VerSe content and code can be accessed at: https://***/anjany/verse. © 2020, CC BY-NC-ND.

关键词： computerized tomography

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Heuristics for evaluating multi-touch gestures in mobile applications 31

Heuristics for evaluating multi-touch gestures in mobile app...

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31st International BCS Human computer Interaction Conference: Digital Make Believe, HCI 2017

作者： Humayoun, Shah Rukh Chotala, Paresh Hamirbhai Bashir, Muhammad Salman Ebert, Achim Computer Graphics HCI Group University of Kaiserslautern Kaiserslautern67663 Germany Department of Computer Science Virtual University of Pakistan Lahore Pakistan

Multi-touch gesture interaction is one of the main features that differentiate the current smart mobile era from the desktop-computing era. Heuristic evaluation is a popular usability evaluation method, mainly due to being less time-consuming, more cost effective, and applicable to different stages of the design and development phases. Researchers have provided their own sets of heuristics targeting domain specific mobile applications or some specific features (e.g., contextual behaviour). In this work, we specifically target evaluating multi-touch gestures in mobile apps through a set of 15 heuristics, which we selected after analysing previously proposed sets of heuristics. However, we adjusted these selected heuristics to make them appropriate for evaluating multi-touch gestures. We conducted a preliminary study with five evaluators in which they were able to find out more usability problems related to multi-touch gestures in the used mobile app compared to a previously proposed heuristics set for mobile apps. © Humayoun et al. Published by BCS Learning and Development Ltd.

关键词： Heuristic methods

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Virtual reality meets smartwatch - Intuitive, natural, and multi-modal interaction

Virtual reality meets smartwatch - Intuitive, natural, and m...

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2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI EA 2017

作者： Rupprecht, Franca Alexandra Ebert, Achim Schneider, Andreas Hamann, Bernd Computer Graphics and HCI University of Kaiserslautern Kaiserslautern Germany Department of Computer Science University of California DavisCA95616 United States

ISBN: (纸本)9781450346566

Despite the fact of increasing popularity virtual environments still lack useful and natural interaction techniques. We present a multi-modal interaction interface, designed for smartwatches and smartphones for fully immersive environments. Our approach enhances the efficiency of interaction in virtual worlds in a natural and intuitive way. We have designed and implemented methods for handling seven gestures and compare our approach with common VR input technology, namely body tracking using a 3D camera. The findings suggest our approach to be very encouraging for further developments. Copyright © 2017 by the Association for Computing Machinery, Inc. (ACM).

关键词： Gesture recognition

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Storage and Processing Technologies of Cognitive Content for eLearning Systems

Storage and Processing Technologies of Cognitive Content for...

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Russia and Pacific Conference on computer Technology and Applications (RPC)

作者： S.V. Tarkhov N.S. Minasova Sh.M. Minasov L.M. Tarkhova Department of Computer Science Ufa State Aviation Technical University Ufa Russia Department of Mechanics and Engineering Graphics Bashkir State Agrarian University Ufa Russia

ISBN: (纸本)9781538675328

Described the technologies of structuring, decomposition, storage organization and personal-oriented assembly of training content in web-oriented open eLearning systems. Hierarchical object-oriented model allows to store decomposed to low-level data and perform automated reconstruction cognitive content provided to trainee in the compiled modules form, that contain training materials and management procedures adaptive eLearning. The technology is used for virtual knowledge space building.

关键词： Electronic learning Training Metadata Shape Object oriented modeling Adaptation models

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Morphable Face Models - An Open Framework

Morphable Face Models - An Open Framework

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International Conference on Automatic Face and Gesture Recognition

作者： Thomas Gerig Andreas Morel-Forster Clemens Blumer Bernhard Egger Marcel Luthi Sandro Schoenborn Thomas Vetter Department of Mathematics and Computer Science Graphics and Vision Research Group Basel Switzerland Dept. of Math. & Comput. Sci. Graphics & Vision Res. Group Basel Switzerland

In this paper, we present a novel open-source pipeline for face registration based on Gaussian processes as well as an application to face image analysis. Non-rigid registration of faces is significant for many applications in computer vision, such as the construction of 3D Morphable face models (3DMMs). Gaussian Process Morphable Models (GPMMs) unify a variety of non-rigid deformation models with B-splines and PCA models as examples. GPMM separate problem specific requirements from the registration algorithm by incorporating domain-specific adaptions as a prior model. The novelties of this paper are the following: (i) We present a strategy and modeling technique for face registration that considers symmetry, multi-scale and spatially-varying details. The registration is applied to neutral faces and facial expressions. (ii) We release an open-source software framework for registration model-building demonstrated on the publicly available BU3D-FE database. The released pipeline also contains an implementation of an Analysis-by-Synthesis model adaption of 2D face images, tested on the Multi-PIE and LFW database. This enables the community to reproduce, evaluate and compare the individual steps of registration to model-building and 3D/2D model fitting. (iii) Along with the framework release, we publish a new version of the Basel Face Model (BFM-2017) with an improved age distribution and an additional facial expression model.

关键词： Face Adaptation models Strain Kernel Shape Deformable models Gaussian processes

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Software infrastructure to reduce the cost and time of building enterprise software applications: Practices and case studies 26

Software infrastructure to reduce the cost and time of build...

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26th International Conference on Software Engineering and Data Engineering, SEDE 2017

作者： Kiswani, Jalal Muhanna, Muhanna Dascalu, Sergiu M. Harris, Frederick C. Department of Computer Science and Engineering University of Nevada Reno RenoNV89503 United States Department of Computer Graphics Princess Sumaya University for Technology Amman Jordan

ISBN: (纸本)9781943436095

In traditional software projects development, there were mandatory activities that should be carried out during the software development life cycle (SDLC). These activities were time-consuming and expensive. They were either performed manually or in basic approaches by different roles. Some of these activities include: version control, project structuring, development environment preparation, software testing, building, packaging, deployment, and management of dependencies including third party libraries and application programming interfaces (APIs). This paper discusses the rationale behind the importance of these activities, and how their automation can reduce the time and cost of software projects, as well as increasing its quality. This paper also consists of some of available open-source resources, and mature free software tools that are already implemented in the software industry of Java technology. Moreover, the paper discusses current limitations of these tools, and includes three case studies of a government and an academic organization, as well as a software development house, at which these recommendations have been implemented. Copyright ISCA, SEDE 2017.

关键词： Software testing

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On interval methods with zero rewriting and exact geometric computation 7th

On interval methods with zero rewriting and exact geometric ...

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7th International Conference on Mathematical Aspects of computer and Information sciences, MACIS 2017

作者： Schirra, Stefan Wilhelm, Martin Department of Simulation and Graphics Faculty of Computer Science University of Magdeburg Universitätsplatz 2 Magdeburg39106 Germany

ISBN: (纸本)9783319724522

We oppose interval-symbol methods with zero rewriting developed by Shirayanagi and Sekigawa [14, 31–33] to the exact geometric computation paradigm [17, 37], especially to exact decisions computation via lazy adaptive evaluation with expression-dags, in doing so carving out analogies and disparities. © Springer International Publishing AG 2017.

关键词： Numerical methods

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Plane-based surface regularization for urban 3D reconstruction 28

Plane-based surface regularization for urban 3D reconstructi...

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28th British Machine Vision Conference, BMVC 2017

作者： Holzmann, Thomas Oswald, Martin R. Pollefeys, Marc Fraundorfer, Friedrich Bischof, Horst Institute of Computer Graphics and Vision Graz University of Technology Graz Austria Department of Computer Science ETH Zurich Zurich Switzerland Microsoft Redmond United States

ISBN: (纸本)190172560X

We propose a method for urban 3D reconstruction that is a hybrid between a volumetric 3D reconstruction approach and a plane fitting approach in order to obtain a denoised and compact representation of the scene. In our hybrid approach, a single global optimization, using visibility as main information, defines whether the final reconstructed surface should align with a detected plane or rather follow the details of the input data. Our method is based on an established tetrahedral occupancy labeling approach which we taylor for urban reconstruction by adding the possibility to favor an alignment of the surface with detected planes. We further add novel regularization terms that favor Manhattan-like structures and which allow to control the level of detail of the output model. A variety of experiments demonstrate state-of-the-art performance and show that our approach is suitable for both indoor and outdoor environments. © 2017. The copyright of this document resides with its authors.

关键词： Global optimization

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Revealing the Invisible: Visual Analytics and Explanatory Storytelling for Advanced Team Sport Analysis

Revealing the Invisible: Visual Analytics and Explanatory St...

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Big Data Visual Analytics (BDVA)

作者： Manuel Stein Thorsten Breitkreutz Johannes Haussler Daniel Seebacher Christoph Niederberger Tobias Schreck Michael Grossniklaus Daniel Keim Halldor Janetzko Department of Computer and Information Science University of Konstanz Germany VIZRT Switzerland Institute for Computer Graphics and Knowledge Visualization Graz University of Technology Austria Universitat Konstanz Konstanz Baden-WÃ¼rttemberg DE Department of Geography University of Zurich Switzerland

ISBN: (纸本)9781538691953

The analysis of invasive team sports often concentrates on cooperative and competitive aspects of collective movement behavior. A main goal is the identification and explanation of strategies, and eventually the development of new strategies. In visual sports analytics, a range of different visual-interactive analysis techniques have been proposed, e.g., based on visualization using for example trajectories, graphs, heatmaps, and animations. Identifying suitable visualizations for a specific situation is key to a successful analysis. Existing systems enable the interactive selection of different visualization facets to support the analysis process. However, an interactive selection of appropriate visualizations is a difficult, complex, and time-consuming task. In this paper, we propose a four-step analytics conceptual workflow for an automatic selection of appropriate views for key situations in soccer games. Our concept covers classification, specification, explanation, and alteration of match situations, effectively enabling the analysts to focus on important game situations and the determination of alternative moves. Combining abstract visualizations with real world video recordings by Immersive Visual Analytics and descriptive storylines, we support domain experts in understanding key situations. We demonstrate the usefulness of our proposed conceptual workflow via two proofs of concept and evaluate our system by comparing our results to manual video annotations by domain experts. Initial expert feedback shows that our proposed concept improves the understanding of competitive sports and leads to a more efficient data analysis.

关键词： Sports Games Data visualization Trajectory Visual analytics Video recording

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