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The use of semantics in the CrossCult H2020 project 2nd

The use of semantics in the CrossCult H2020 project

2nd COST Action IC1302 International KEYSTONE Conference on Semantic Keyword-Based Search on Structured Data Sources, IKC 2016

作者： Bampatzia, Stavroula Bravo-Quezada, Omar Gustavo Antoniou, Angeliki Nores, Martín López Wallace, Manolis Lepouras, George Vassilakis, Costas Human-Computer Interaction and Virtual Reality Lab Department of Informatics and Telecommunications University of the Peloponnese Tripolis22 131 Greece GIHP4C Research Group Universidad Politécnica Salesiana Cuenca Ecuador Department of Telematics Engineering AtlantTIC Research Centre University of Vigo Vigo Spain Knowledge and Uncertainty Research Laboratory Department of Informatics and Telecommunications University of the Peloponnese Tripolis22 131 Greece

ISBN: (纸本)9783319536392

CrossCult is a newly started project that aims to make reflective history a reality in the European cultural context. In this paper we examine how the project aims to take advantage of advances in semantic technologies in order to achieve its goals. Specifically, we see what the quest for reflection is and, through practical examples from two of the project’s flagship pilots, explain how semantics can assist in this direction. © Springer International Publishing AG 2017.

关键词： Semantics

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Evaluation of algorithms for multi-modality whole heart segmentation: An open-access grand challenge

arXiv

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arXiv 2019年

作者： Zhuang, Xiahai Li, Lei Payer, Christian Štern, Darko Urschler, Martin Heinrich, Mattias P. Oster, Julien Wang, Chunliang Smedby, Örjan Bian, Cheng Yang, Xin Heng, Pheng-Ann Mortazi, Aliasghar Bagci, Ulas Yang, Guanyu Sun, Chenchen Galisot, Gaetan Ramel, Jean-Yves Brouard, Thierry Tong, Qianqian Si, Weixin Liao, Xiangyun Zeng, Guodong Shi, Zenglin Zheng, Guoyan Wang, Chengjia MacGillivray, Tom Newby, David Rhode, Kawal Ourselin, Sebastien Mohiaddin, Raad Keegan, Jennifer Firmin, David Yang, Guang School of Data Science Fudan University Shanghai200433 China Fudan-Xinzailing Joint Research Center for Big Data Fudan University Shanghai200433 China School of Biomedical Engineering Shanghai Jiao Tong University Shanghai200240 China Institute of Computer Graphics and Vision Graz University of Technology Graz8010 Austria Ludwig Boltzmann Institute for Clinical Forensic Imaging Graz8010 Austria Institute of Medical Informatics University of Lubeck Lubeck23562 Germany Inserm Université de Lorraine U1254 IADI Nancy France School for Technology and Health KTH Royal Institute of Technology StockholmSE-10044 Sweden School of Biomed. Eng. Health Science Centre Shenzhen University Shenzhen518060 China Dept. of Comp. Sci. and Eng. Chinese University of Hong Kong Hong Kong China University of Central Florida Orlando32816 United States School of Computer Science and Engineering Southeast University Nanjing210096 China Université de Tours 64 avenue Jean Portalis Tours37200 France School of Computer Science Wuhan University Wuhan430072 China Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology SIAT Shenzhen China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Institute for Surgical Technology & Biomechanics University of Bern Bern3014 Switzerland BHF Centre for Cardiovascular Science University of Edinburgh Edinburgh United Kingdom Edinburgh Imaging Facility QMRI University of Edinburgh Edinburgh United Kingdom Department of Imaging Sciences & Biomedical Engineering Kings College London London United Kingdom Cardiovascular Research Centre Royal Brompton Hospital LondonSW3 6NP United Kingdom National Heart and Lung Institute Imperial College London London LondonSW7 2AZ United Kingdom

Knowledge of whole heart anatomy is a prerequisite for many clinical applications. Whole heart segmentation (WHS), which delineates substructures of the heart, can be very valuable for modeling and analysis of the anatomy and functions of the heart. However, automating this segmentation can be arduous due to the large variation of the heart shape, and different image qualities of the clinical data. To achieve this goal, a set of training data is generally needed for constructing priors or for training. In addition, it is difficult to perform comparisons between different methods, largely due to differences in the datasets and evaluation metrics used. This manuscript presents the methodologies and evaluation results for the WHS algorithms selected from the submissions to the Multi-Modality Whole Heart Segmentation (MM-WHS) challenge, in conjunction with MICCAI 2017. The challenge provides 120 three-dimensional cardiac images covering the whole heart, including 60 CT and 60 MRI volumes, all acquired in clinical environments with manual delineation. Ten algorithms for CT data and eleven algorithms for MRI data, submitted from twelve groups, have been evaluated. The results show that many of the deep learning (DL) based methods achieved high accuracy, even though the number of training datasets were limited. A number of them also reported poor results in the blinded evaluation, probably due to overfitting in their training. The conventional algorithms, mainly based on multi-atlas segmentation, demonstrated robust and stable performance, even though the accuracy is not as good as the best DL method in CT segmentation. The challenge, including provision of the annotated training data and the blinded evaluation for submitted algorithms on the test data, continues as an ongoing benchmarking resource via its homepage (***/zhuangxiahai/0/mmwhs/). Copyright © 2019, The Authors. All rights reserved.

关键词： Heart

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Using social media to stimulate history reflection in cultural heritage

Using social media to stimulate history reflection in cultur...

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International Workshop on Semantic Media Adaptation and Personalization (SMAP)

作者： Stavroula Bampatzia Angeliki Antoniou George Lepouras Costas Vasilakis Manolis Wallace Department of Informatics and Telecommunications Human-Computer Interaction and Virtual Reality Lab Tripolis Greece Department of Informatics and Telecommunications Knowledge and Uncertainty Research Laboratory Tripolis Greece

CrossCult H2020 is a European project, the aim of which is the reflection of history in a cultural setting. In this paper, we describe how social media can be linked to cultural heritage and in particular how we can incorporate games, social networks, history reflection and culture. The paper presents the case study of one of the project pilots, to show how history reflection can be enhanced with the use of social networks.

关键词： Reflection Cultural differences History Games Facebook Europe

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Interconnecting objects, visitors, sites and (Hi)stories across cultural and historical concepts: The crosscult project 6th

Interconnecting objects, visitors, sites and (Hi)stories acr...

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6th International Euro-Mediterranean Conference on Digital Heritage, EuroMed 2016

作者： Vassilakis, Costas Antoniou, Angeliki Lepouras, George Wallace, Manolis Lykourentzou, Ioanna Naudet, Yannick Human-Computer Interaction and Virtual Reality Lab Department of Informatics and Telecommunications University of the Peloponnese Tripolis22 131 Greece Knowledge and Uncertainty Research Laboratory Department of Informatics and Telecommunications University of the Peloponnese Tripolis22 131 Greece Luxembourg Institute of Science and Technology 5 avenue des Hauts-Fourneaux Esch/Alzette4363 Luxembourg

ISBN: (纸本)9783319484952

Human History, is a huge mesh of interrelated facts and concepts, spanning beyond borders, encompassing global aspects and finally constituting a shared, global experience. This is especially the case regarding European history, which is highly interconnected by nature;however, most History-related experiences that are today offered to the greater public, from schools to museums, are siloed. The CrossCult project aims to provide the means for offering citizens and cultural venue visitors a more holistic view of history, in the light of cross-border interconnections among pieces of cultural heritage, other citizens viewpoints and physical venues. To this end, the CrossCult project will built a comprehensive knowledge base encompassing information and semantic relationships across cultural information elements, and will provide the technological means for delivering the contents of this knowledge base to citizens and venue visitors in a highly personalized manner, creating narratives for the interactive experiences that maximise situational curiosity and serendipitous learning. The CrossCult platform will also exploit the cognitive/emotional profiles of the participants as well as temporal, spatial and miscellaneous features of context, including holidays and anniversaries, social media trending topics and so forth. © Springer International Publishing AG 2016.

关键词： Semantics

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Synthesizing and editing dynamic flames with color temperature

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Chinese Science Bulletin 2014年第36期59卷 5379-5392页

作者： Zhaohui Wu Zhong Zhou Fei Dou Ye Duan Wei Wu State Key Laboratory of Virtual Reality Technology and Systems Beihang University Computer Graphics and Image Understanding Laboratory University of Missouri Columbia MO 65211 USA

Generating computer animated flames is a difficult and computationally expensive problem. Dynamic textures provide an effective means for extrapolating and synthesizing dynamic flames, but aggravates color distortion due to the high correlation of RGB components. A novel method for dynamic flame texture synthesis using color temperature is proposed in this paper. Firstly, the colortemperature mapping is calculated by using the Planck's law and two-color pyrometric technique to avoid color distortion. Secondly, a novel dynamic texture model is presented to transform the RGB space into temperature space. Finally,the dynamic flames editing is presented to support physical temperature adjustment. Experimental results illustrate that our approach is effective to synthesize visually plausible dynamic flames without color distortions and to edit dynamic flames with intuitive physical interpretation.

关键词：纹理合成火焰色温编辑 RGB空间计算问题彩色失真温度调节

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Multi-task rank learning for image quality assessment 40

Multi-task rank learning for image quality assessment

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40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015

作者： Xu, Long Li, Jia Lin, Weisi Zhang, Yongbing Ma, Lin Fang, Yuming Zhang, Yun Yan, Yihua Key Laboratory of Solar Activity National Astronomical Observatories Chinese Academy of Sciences Beijing China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering BeihangUniversity Beijing China International Research Institute for Multidisciplinary Science Beihang University Beijing China Department of Computer Engineering Nanyang Technological University Singapore Graduate School at Shenzhen Tsinghua University Shenzhen China Huawei Noah's Ark Lab Hong Kong School of Information Technology Jiangxi University of Finance and Economics Nanchang China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China

ISBN: (纸本)9781467369978

In practice, multiple types of distortions are associated with an image quality degradation process. The existing machine learning (ML) based image quality assessment (IQA) approaches generally established a unified model for all distortion types, or each model is trained independently for each distortion type by using single-task learning, which lead to the poor generalization ability of the models as applied to practical image processing. There are often the underlying cross relatedness amongst these single-task learnings in IQA, which is ignored by the previous approaches. To solve this problem, we propose a multi-task learning framework to train IQA models simultaneously across individual tasks each of which concerns one distortion type. These relatedness can be therefore exploited to improve the generalization ability of IQA models from single-task learning. In addition, pairwise image quality rank instead of image quality rating is optimized in learning task. By mapping image quality rank to image quality rating, a novel no-reference (NR) IQA approach can be derived. The experimental results confirm that the proposed Multi-task Rank Learning based IQA (MRLIQ) approach is prominent among all state-of-the-art NR-IQA approaches. © 2015 IEEE.

关键词： image quality assessment machine learning MOS pairwise comparison Rank learning

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A generalized God-object method for plausible finger-based interactions in virtual environments

A generalized God-object method for plausible finger-based i...

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7th International IEEE Symposium on 3D User Interfaces 2012, 3DUI 2012

作者： Jacobs, Jan Stengel, Michael Froehlich, Bernd Group Research Virtual Technologies Volkswagen AG Germany Computer Graphics Lab TU Braunschweig Germany Virtual Reality Systems Group Bauhaus-Universität Weimar Germany

ISBN: (纸本)9781467312059

We generalize the six degree-of-freedom God-object approach to enable its use for multi-finger interactions in virtual environments. The connected finger phalanxes are modeled as multiple constrained God objects. The mutual interdependencies between multiple God objects are resolved using Gauss' principle of least constraint. This generalization of the God-object method allows us to avoid the penetration of multiple fingers and their phalanxes with objects within a physically simulated virtual world. Our observations indicate that the generalized God-object approach leads to plausible collision-free positions and motions of the phalanxes of the user's fingers during complex six degree-of-freedom manipulations, while artifacts such as artificial friction or a stuck hand are avoided. © 2012 IEEE.

关键词： virtual reality

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A generalized God-object method for plausible finger-based interactions in virtual environments

A generalized God-object method for plausible finger-based i...

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IEEE Symposium on 3D User Interfaces (3DUI)

作者： Jan Jacobs Michael Stengel Bernd Froehlich Group Research Virtual Technologies Volkswagen AG Germany Computer Graphics Laboratory Technical University of Braunschweig Germany Virtual Reality Systems Group Bauhaus-Universität Weimar Germany

关键词： Mathematical model Acceleration Equations Jacobian matrices Vectors Haptic interfaces Computational modeling

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Finger vein verification using Occurrence Probability Matrix (OPM)

Finger vein verification using Occurrence Probability Matrix...

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International Joint Conference on Neural Networks

作者： Darun Tang Beining Huang Rongfeng Li Wenxin Li Xiaoming Li Key Laboratory of Machine Perception (MOE) School of Electronics Engineering and Computer Science Peking University State Key Lab of Virtual Reality Technology and Systems Beihang University

ISBN: (纸本)9781467314886

We found that the discrepancy between different finger vein templates of the same finger affects the identification results more seriously than the similarity of templates of different fingers does. Some areas on templates have stable values while some other areas are variable. We propose the Occurrence Probability Matrix (OPM), which is a property of a finger, to define the stability. When matching two templates using OPM, the areas of higher stability make more contribution to the result and those of lower stability make less contribution. In this way, OPM can enhance the similarity of templates of the same finger and drop off the influence of the unsteady areas. In a finger vein verification system running for a long time, we can get enough templates of every finger to generate an effective OPM. But it does not mean that using more templates can get a better OPM. So, we fatherly propose a strategy to select typical templates purposely from all templates of a finger to calculate the OPM. Experimental results show that by simply using OPM calculated from all existing templates, the EER of the system is reduced from 9.8% to 7.6%. And by using the OPM calculated from selected typical templates by our strategy, the EER of the system is further reduced from 7.6% to 3.1%.

关键词： OPM Finger vein Template Stability Selection

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Resource-distortion modeling for video streaming over mesh networks with priority-based packet scheduling

Resource-distortion modeling for video streaming over mesh n...

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2012 13th IEEE International Conference on Multimedia and Expo, ICME 2012

作者： Zhang, Yongfei Zhang, Yunsheng Qin, Shiyin He, Zhihai Beijing Key Lab. of Digital Media School of Computer Science and Engineering Beihang University Beijing 100191 China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing 100191 China School of Automation Science and Electrical Engineering Beihang University Beijing 100191 China Graduate School at Shenzhen Tsinghua University Shenzhen 518055 China Department of Electrical and Computer Engineering University of Missouri Columbia MO 65211 United States

ISBN: (纸本)9781467316590

Video streaming over mesh networks operates under stringent network resource constraints, with a large number of video sessions competing for limited network resources. In this work, we aim to establish so-called resource-distortion models to characterize the inherent relationship between the allocated network resources to each video session and its end-to-end video distortion or presentation quality at the receiver end. We observed that priority-based packet scheduling has significant impact on such resource-distortion relationship. Using ANN-based learning methods, we develop an end-to-end packet delay bound violation (PDBV) probability model for video streaming over multi-hop networks with priority-based packet scheduling. We then derive a quadratic video transmission distortion model to capture the unique behavior of priority-based packet scheduling and its impact on the end-to-end video distortion. Based on these resource-distortion models, we are able to predict the end-to-end distortion for video streaming over multi-hop networks with priority-based packet scheduling. Our extensive experimental results demonstrate that the proposed method is very accurate. © 2012 IEEE.

关键词： Video streaming

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