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IEEE Access 2024年 12卷 i-xi页

作者： Derek Abbott Sonia Aissa Anuradha Annaswamy Nirwan Ansari Jun Cai Kun-Shan Chen Yixin Chen J.-C. Chiao Ayman El-Baz Shaikh Fattah Hoay Gooi Maya Gokhale Chih-Lin Ⅰ Giuseppe Iannaccone Yumi Iwashita Bruce Jacob Abbas Jamalipour Bahram Javidi Weihua Jiang Okyay Kaynak Hulya Kirkici Germano Lambert-Torres Shengtao Li Michal Mrozowski Michele Nappi Dalma Novak Hugo Proença Yi Qian Zhihua Qu Susanto Rahardja Mehrdad Saif Ali Serpengüzel Peter H. Siegel Ashitey Trebi-Ollennu Daniela Tuninetti Ge Wang Keith A. Wear Andreas Weisshaar C. Patrick Yue Enrico Zio School of Electrical and Electronic Engineering University of Adelaide Adelaide SA Australia Institut National de la Recherche Scientifique (INRS) Québec City Canada Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge MA USA Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA Concordia University Montreal Canada Guilin University of Technology Guilin China Washington University St. Louis MO USA Southern Methodist University Dallas TX USA University of Louisville/Bioengineering Department Louisville KY USA Department of Electrical and Electronic Engineering Bangladesh University of Engineering and Technology Dhaka Bangladesh Nanyang Technological University Jurong West Singapore Lawrence Livermore National Laboratory Livermore CA USA China Mobile Research Institute Beijing China University of Pisa Pisa Italy NASA-JPL California Institute of Technology Pasadena CA USA Florida Polytechnic University Lakeland FL USA The University of Sydney Sydney NSW Australia University of Connecticut Storrs CT USA Nagaoka University of Technology Nagaoka Niigata Japan Department of Electrical and Electronic Engineering Boğaziçi University Istanbul Turkey University of South Alabama Mobile AL USA Gnarus Institute Itajuba Brazil Xi’an Jiaotong University Xi’an China Gdansk University of Technology Gdansk Poland University of Salerno Fisciano Italy Octane Wireless Hanover MD USA University of Beira Interior Covilhã Portugal Department of Electrical and Computer Engineering University of NebraskaLincoln Lincoln NE USA University of Central Florida Orlando Florida USA Singapore Institute of Technology 10 Dover Dr Singapore Infocomm Technology Cluster 10 Dover Dr Singapore University of Windsor Windsor Canada Department of Physics Koç University Istanbul Turkey California Institute of Technology (CalTech) Pasadena California USA NASA-JPL Mobility and Robotics Systems S

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Attention-based active visual search for mobile robots

arXiv

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arXiv 2018年

作者： Rasouli, Amir Lanillos, Pablo Cheng, Gordon Tsotsos, John K. The Department of Electrical Engineering and Computer Science Center for Vision Research York University Toronto Canada Technische Universität München Institute for Cognitive Systems Arcisstraße 21 München80333 Germany

We present an active visual search model for finding objects in unknown environments. The proposed algorithm guides the robot towards the sought object using the relevant stimuli provided by the visual sensors. Existing search strategies are either purely reactive or use simplified sensor models that do not exploit all the visual information available. In this paper, we propose a new model that actively extracts visual information via visual attention techniques and, in conjunction with a non-myopic decision-making algorithm, leads the robot to search more relevant areas of the environment. The attention module couples both top-down and bottom-up attention models enabling the robot to search regions with higher importance first. The proposed algorithm is evaluated on a mobile robot platform in a 3D simulated environment. The results indicate that the use of visual attention significantly improves search, but the degree of improvement depends on the nature of the task and the complexity of the environment. In our experiments, we found that performance enhancements of up to 42% in structured and 38% in highly unstructured cluttered environments can be achieved using visual attention mechanisms. Copyright © 2018, The Authors. All rights reserved.

关键词： Mobile robots

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Multicast Repair for Broadcast Flows to the Handheld Receivers

Multicast Repair for Broadcast Flows to the Handheld Receive...

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IEEE Wireless Communications and Networking Conference

作者： Muhammad Moiz Anis Luis Suarez Johann Leithon Dushantha Nalin K. Jayakody School of Science and Engineering Habib University Karachi Pakistan Huawei Technologies Co Ltd Russian Research Center Moscow Russia Department of Signal Processing and Acoustics Aalto University Espoo Finland School of Computer Science and Robotics National Research Polytechnic University Tomsk Russia

Mobile TV receivers operate with a weaker link budget in the Digital Video Broadcast (DVB) network compared to the fixed rooftop mounted antenna receivers. Nevertheless, the cellular radio interface is an attractive alternative for broadcast services given its reliability. In this work, we use Long Term Evolution (LTE) 's evolved Multimedia Broadcast Multicast Service (eMBMS) to multicast overhead parity packets among the multicast groups of mobile TV receivers (e.g. smartphones suffering from DVB packet erasures). The proposed multicast scheme recovers erased packets at each smartphone by Systematic RaptorQ Code (SRQC) decoding the directly received DVB transmission along with the overhead packets transmitted via eMBMS multicast. We analyze the load generated in the Cellular Radio Access Network due to this erasure-recovery multicast scheme and compare the gains of such a service over the LTE unicast retransmissions of the missing DVB packets.

关键词： Mobile TV EMBMS Block codes Multicast repair DVB-T2 LTE Real-time broadcast Multicast Linear combinations Erasure channel

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AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results 16th

AIM 2020 Challenge on Real Image Super-Resolution: Methods a...

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Workshops held at the 16th European Conference on computer vision, ECCV 2020

作者： Wei, Pengxu Lu, Hannan Timofte, Radu Lin, Liang Zuo, Wangmeng Pan, Zhihong Li, Baopu Xi, Teng Fan, Yanwen Zhang, Gang Liu, Jingtuo Han, Junyu Ding, Errui Xie, Tangxin Cao, Liang Zou, Yan Shen, Yi Zhang, Jialiang Jia, Yu Cheng, Kaihua Wu, Chenhuan Lin, Yue Liu, Cen Peng, Yunbo Zou, Xueyi Luo, Zhipeng Yao, Yuehan Xu, Zhenyu Zamir, Syed Waqas Arora, Aditya Khan, Salman Hayat, Munawar Khan, Fahad Shahbaz Ahn, Keon-Hee Kim, Jun-Hyuk Choi, Jun-Ho Lee, Jong-Seok Zhao, Tongtong Zhao, Shanshan Han, Yoseob Kim, Byung-Hoon Baek, JaeHyun Wu, Haoning Xu, Dejia Zhou, Bo Guan, Wei Li, Xiaobo Ye, Chen Li, Hao Zhong, Haoyu Shi, Yukai Yang, Zhijing Yang, Xiaojun Li, Xin Jin, Xin Wu, Yaojun Pang, Yingxue Liu, Sen Liu, Zhi-Song Wang, Li-Wen Li, Chu-Tak Cani, Marie-Paule Siu, Wan-Chi Zhou, Yuanbo Umer, Rao Muhammad Micheloni, Christian Cong, Xiaofeng Gupta, Rajat Ahn, Keon-Hee Kim, Jun-Hyuk Choi, Jun-Ho Lee, Jong-Seok Almasri, Feras Vandamme, Thomas Debeir, Olivier Sun Yat-sen University Guangzhou China Harbin Institute of Technology University Harbin China Computer Vision Lab ETH Zurich Zurich Switzerland Baidu Research Silicon Valley United States Baidu Incorportation Silicon Valley United States China Electronic Technology Cyber Security Co. Ltd. Beijing China Guangdong OPPO Mobile Telecommunications Corp. Ltd. Dongguan China NetEase Games AI Lab Beijing China Noah’s Ark Lab Huawei Beijing China Co. Ltd. Shanghai China Beijing China Yonsei University Seodaemun-gu Korea Republic of Dalian Maritime Univerity Dalian China New Mexico United States Daejeon Korea Republic of Seattle United States Peking University Beijing China Jiangnan University Jiangnan China Karlsruher Institut fuer Technologie Karlsruher Germany Tongji University Tongji China Guangdong University of Technology Tongji China University of Science and Technology of China Hefei China Palaiseau France Center of Multimedia Signal Processing The Hong Kong Polytechnic University Hong Kong China Fuzhou University Fuzhou Fujian China University of Udine Udine Italy Indian Institute of Technology Khargapur India National University of Defense Technology Changsha China LISA Department Universie Libre de Bruxelles Brussels Belgium

ISBN: (纸本)9783030670696

This paper introduces the real image Super-Resolution (SR) challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ECCV 2020. This challenge involves three tracks to super-resolve an input image for × 2, × 3 and × 4 scaling factors, respectively. The goal is to attract more attention to realistic image degradation for the SR task, which is much more complicated and challenging, and contributes to real-world image super-resolution applications. 452 participants were registered for three tracks in total, and 24 teams submitted their results. They gauge the state-of-the-art approaches for real image SR in terms of PSNR and SSIM. © 2020, Springer Nature Switzerland AG.

关键词： Optical resolving power

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Limited Knowledge of Safe Driving Practice among Drivers with Diabetes in Armenia: Association with Greater Risk of Motor Vehicle Accidents

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Journal of Diabetes Mellitus 2019年第1期9卷 14-23页

作者： Lilit Petrosyan Zhanna Ghazaryan Greta Muradyan Elena Aghajanova Marek Brabece Denisa Janickova Zdarska Katarina Halciakova Jan Polak Brian MFrier Jan Broz N8 Policlinic Yerevan State Medical UniversityYerevanArmenia “SourbAstvatsamayr”Medical Centers YerevanArmenia Armenian-American Wellness Center YerevanArmenia Department of Endocrinology Yerevan State Medical University“Muratsan”University HospitalYerevanArmenia Institute of Computer Science The Czech Academy of SciencesPragueCzech Republic Czech Institute of Informatics Roboticsand CyberneticsCzech Technical University in PraguePragueCzech Republic Department of Internal Medicine Second Medical Faculty of Charles UniversityPragueCzech Republic Department for the Study of Obesity and Diabetes Third Medical Faculty of Charles UniversityPragueCzech Republic British Heart Foundation Centre for Cardiovascular Science The Queen’s Medical Research InstituteUniversity of EdinburghEdinburghUK

Aims: The aims of the study were to assess the degree of knowledge and adherence to the recommended safe practice for driving and the risk of road traffic accidents among people with diabetes mellitus in Armenia. Methods: A total of 628 respondents, including 200 drivers, out of 641 consecutive attendees at six diabetes clinics, participated in the survey. A modified British questionnaire on driving and diabetes was used to obtain the relevant data. The information from all 103 drivers treated with insulin and 73 taking sulfonylureas was reviewed. Results: The study revealed that of 176 insulin and sulfonylurea-treated drivers, 161 (91.5%) had never received any advice about safe driving practices. Among the drivers, 156 (88.6%) never measured their blood glucose before, or during driving. The survey revealed that 86 (51.2%) of 168 patients had a history of at least one motor vehicle accident within the previous 5 years. The average road traffic accident rate per person/year was 0.21. Conclusions: The study revealed a lack of knowledge among drivers with diabetes treated with insulin or sulfonylureas concerning recommended safe practices for driving. This was associated with significant hypoglycemia while driving and an elevated rate of road traffic accidents.

关键词： Driving Hypoglycemia Road Traffic Accident

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Explaining first impressions: Modeling, recognizing, and explaining apparent personality from videos

arXiv

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arXiv 2018年

作者： Escalante, Hugo Jair Kaya, Heysem Salah, Albert Ali Escalera, Sergio Güçlütürk, Yağmur Güçlü, Umut Baró, Xavier Guyon, Isabelle Jacques, Julio Madadi, Meysam Ayache, Stephane Viegas, Evelyne Gürpınar, Furkan Wicaksana, Achmadnoer Sukma Liem, Cynthia C.S. van Gerven, Marcel A.J. van Lier, Rob INAOE Mexico ChaLearn United States Namık Kemal University Department of Computer Engineering Turkey Bogaziçi University Dept. of Computer Engineering Turkey and Nagoya University FCVRC Japan Bogaziçi University Computational Science and Engineering Turkey University of Barcelona and Computer Vision Center Spain Computer Vision Center Spain Radboud University Donders Institute for Brain Cognition and Behaviour Nijmegen Netherlands Universitat Oberta de Catalunya and Computer Vision Center Spain UPSud/INRIA Université Paris-Saclay France Aix Marseille Univ CNRS LIF Marseille France Microsoft Research United States Multimedia Computing Group Delft University of Technology Delft Netherlands

Explainability and interpretability are two critical aspects of decision support systems. Within computer vision, they are critical in certain tasks related to human behavior analysis such as in health care applications. Despite their importance, it is only recently that researchers are starting to explore these aspects. This paper provides an introduction to explainability and interpretability in the context of computer vision with an emphasis on looking at people tasks. Specifically, we review and study those mechanisms in the context of first impressions analysis. To the best of our knowledge, this is the first effort in this direction. Additionally, we describe a challenge we organized on explainability in first impressions analysis from video. We analyze in detail the newly introduced data set, evaluation protocol, proposed solutions and summarize the results of the challenge. Finally, derived from our study, we outline research opportunities that we foresee will be decisive in the near future for the development of the explainable computer vision field. Copyright © 2018, The Authors. All rights reserved.

关键词： Decision support systems

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Author Correction: The power of genetic diversity in genome-wide association studies of lipids

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Nature 2023年第7965期618卷 E19-E20页

作者： Sarah E Graham Shoa L Clarke Kuan-Han H Wu Stavroula Kanoni Greg J M Zajac Shweta Ramdas Ida Surakka Ioanna Ntalla Sailaja Vedantam Thomas W Winkler Adam E Locke Eirini Marouli Mi Yeong Hwang Sohee Han Akira Narita Ananyo Choudhury Amy R Bentley Kenneth Ekoru Anurag Verma Bhavi Trivedi Hilary C Martin Karen A Hunt Qin Hui Derek Klarin Xiang Zhu Gudmar Thorleifsson Anna Helgadottir Daniel F Gudbjartsson Hilma Holm Isleifur Olafsson Masato Akiyama Saori Sakaue Chikashi Terao Masahiro Kanai Wei Zhou Ben M Brumpton Humaira Rasheed Sanni E Ruotsalainen Aki S Havulinna Yogasudha Veturi QiPing Feng Elisabeth A Rosenthal Todd Lingren Jennifer Allen Pacheco Sarah A Pendergrass Jeffrey Haessler Franco Giulianini Yuki Bradford Jason E Miller Archie Campbell Kuang Lin Iona Y Millwood George Hindy Asif Rasheed Jessica D Faul Wei Zhao David R Weir Constance Turman Hongyan Huang Mariaelisa Graff Anubha Mahajan Michael R Brown Weihua Zhang Ketian Yu Ellen M Schmidt Anita Pandit Stefan Gustafsson Xianyong Yin Jian'an Luan Jing-Hua Zhao Fumihiko Matsuda Hye-Mi Jang Kyungheon Yoon Carolina Medina-Gomez Achilleas Pitsillides Jouke Jan Hottenga Gonneke Willemsen Andrew R Wood Yingji Ji Zishan Gao Simon Haworth Ruth E Mitchell Jin Fang Chai Mette Aadahl Jie Yao Ani Manichaikul Helen R Warren Julia Ramirez Jette Bork-Jensen Line L Kårhus Anuj Goel Maria Sabater-Lleal Raymond Noordam Carlo Sidore Edoardo Fiorillo Aaron F McDaid Pedro Marques-Vidal Matthias Wielscher Stella Trompet Naveed Sattar Line T Møllehave Betina H Thuesen Matthias Munz Lingyao Zeng Jianfeng Huang Bin Yang Alaitz Poveda Azra Kurbasic Claudia Lamina Lukas Forer Markus Scholz Tessel E Galesloot Jonathan P Bradfield E Warwick Daw Joseph M Zmuda Jonathan S Mitchell Christian Fuchsberger Henry Christensen Jennifer A Brody Mary F Feitosa Mary K Wojczynski Michael Preuss Massimo Mangino Paraskevi Christofidou Niek Verweij Jan W Benjamins Jorgen Engmann Rachel L Kember Roderick C Slieker Ken Sin Lo Nuno R Zilhao Phuong Le Marcus E Kleber Graciela E Delgado Shaofeng Huo Dai Department of Internal Medicine Division of Cardiology University of Michigan Ann Arbor MI USA. VA Palo Alto Health Care System Palo Alto CA USA. Department of Medicine Division of Cardiovascular Medicine Stanford University School of Medicine Stanford CA USA. Department of Computational Medicine and Bioinformatics University of Michigan Ann Arbor MI USA. William Harvey Research Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London London UK. Department of Biostatistics and Center for Statistics Genetics University of Michigan Ann Arbor MI USA. Department of Genetics Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Clinical Pharmacology William Harvey Research Institute Barts and The London School of Medicine and Dentistry Queen Mary University of London London UK. Endocrinology Boston Children's Hospital Boston MA USA. Medical and Population Genetics Broad Institute Cambridge MA USA. Department of Genetic Epidemiology University of Regensburg Regensburg Germany. McDonnell Genome Institute and Department of Medicine Washington University St Louis MO USA. Department of Precision Medicine Division of Genome Science National Institute of Health Cheongju-si South Korea. Tohoku Medical Megabank Organization Tohoku University Sendai Japan. Sydney Brenner Institute for Molecular Bioscience Faculty of Health Sciences University of the Witwatersrand Johannesburg South Africa. Center for Research on Genomics and Global Health National Human Genome Research Institute National Institutes of Health Bethesda MD USA. Blizard Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London London UK. Wellcome Sanger Institute Hinxton UK. Department of Epidemiology Emory University Rollins School of Public Health Atlanta GA USA. Atlanta VA Health Care System Decatur GA USA. Malcolm Randall VA Medical Center Gainesville FL USA. Division of Vascular Sur

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Author Correction: Federated learning enables big data for rare cancer boundary detection

引用

Nature communications 2023年第1期14卷 436页

作者： Sarthak Pati Ujjwal Baid Brandon Edwards Micah Sheller Shih-Han Wang G Anthony Reina Patrick Foley Alexey Gruzdev Deepthi Karkada Christos Davatzikos Chiharu Sako Satyam Ghodasara Michel Bilello Suyash Mohan Philipp Vollmuth Gianluca Brugnara Chandrakanth J Preetha Felix Sahm Klaus Maier-Hein Maximilian Zenk Martin Bendszus Wolfgang Wick Evan Calabrese Jeffrey Rudie Javier Villanueva-Meyer Soonmee Cha Madhura Ingalhalikar Manali Jadhav Umang Pandey Jitender Saini John Garrett Matthew Larson Robert Jeraj Stuart Currie Russell Frood Kavi Fatania Raymond Y Huang Ken Chang Carmen Balaña Jaume Capellades Josep Puig Johannes Trenkler Josef Pichler Georg Necker Andreas Haunschmidt Stephan Meckel Gaurav Shukla Spencer Liem Gregory S Alexander Joseph Lombardo Joshua D Palmer Adam E Flanders Adam P Dicker Haris I Sair Craig K Jones Archana Venkataraman Meirui Jiang Tiffany Y So Cheng Chen Pheng Ann Heng Qi Dou Michal Kozubek Filip Lux Jan Michálek Petr Matula Miloš Keřkovský Tereza Kopřivová Marek Dostál Václav Vybíhal Michael A Vogelbaum J Ross Mitchell Joaquim Farinhas Joseph A Maldjian Chandan Ganesh Bangalore Yogananda Marco C Pinho Divya Reddy James Holcomb Benjamin C Wagner Benjamin M Ellingson Timothy F Cloughesy Catalina Raymond Talia Oughourlian Akifumi Hagiwara Chencai Wang Minh-Son To Sargam Bhardwaj Chee Chong Marc Agzarian Alexandre Xavier Falcão Samuel B Martins Bernardo C A Teixeira Flávia Sprenger David Menotti Diego R Lucio Pamela LaMontagne Daniel Marcus Benedikt Wiestler Florian Kofler Ivan Ezhov Marie Metz Rajan Jain Matthew Lee Yvonne W Lui Richard McKinley Johannes Slotboom Piotr Radojewski Raphael Meier Roland Wiest Derrick Murcia Eric Fu Rourke Haas John Thompson David Ryan Ormond Chaitra Badve Andrew E Sloan Vachan Vadmal Kristin Waite Rivka R Colen Linmin Pei Murat Ak Ashok Srinivasan J Rajiv Bapuraj Arvind Rao Nicholas Wang Ota Yoshiaki Toshio Moritani Sevcan Turk Joonsang Lee Snehal Prabhudesai Fanny Morón Jacob Mandel Konstantinos Kamnitsas Ben Glocker Luke V M Dixon Matthew Williams Peter Zamp Center for Biomedical Image Computing and Analytics (CBICA) University of Pennsylvania Philadelphia PA USA. Department of Radiology Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Informatics Technical University of Munich Munich Bavaria Germany. Intel Corporation Santa Clara CA USA. Department of Neuroradiology Heidelberg University Hospital Heidelberg Germany. Clinical Cooperation Unit Neuropathology German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ) Heidelberg Germany. Department of Neuropathology Heidelberg University Hospital Heidelberg Germany. Division of Medical Image Computing German Cancer Research Center Heidelberg Germany. Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Heidelberg Germany. Neurology Clinic Heidelberg University Hospital Heidelberg Germany. Department of Radiology & Biomedical Imaging University of California San Francisco San Francisco CA USA. Symbiosis Center for Medical Image Analysis Symbiosis International University Pune Maharashtra India. Department of Neuroimaging and Interventional Radiology National Institute of Mental Health and Neurosciences Bangalore Karnataka India. Department of Radiology School of Medicine and Public Health University of Wisconsin Madison WI USA. Department of Medical Physics School of Medicine and Public Health University of Wisconsin Madison WI USA. Leeds Teaching Hospitals Trust Department of Radiology Leeds UK. Department of Radiology Brigham and Women's Hospital Harvard Medical School Boston MA USA. Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Charlestown MA USA. Catalan Institute of Oncology Badalona Spain. Consorci MAR Parc de Salut de Barcelona Catalonia Spain. Department of Radiology (IDI

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Webizing interactive CAD review system using super multiview autostereoscopic displays 19th

Webizing interactive CAD review system using super multiview...

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19th International Conference on Human-computer Interaction, HCI International 2017

作者： Seo, Daeil Lee, Yongjae Yoo, Byounghyun Center for Imaging Media Research Korea Institute of Science and Technology Seoul Korea Republic of Department of Computer Science and Engineering Seoul National University of Science and Technology Seoul Korea Republic of Department of HCI and Robotics University of Science and Technology Daejeon Korea Republic of

ISBN: (纸本)9783319587523

A glasses-free super multi-view display has emerged alongside the development of optical technologies. However, the display is not yet widely used because its content remains in the early stages of only image or video without user interaction. Expanding the display market would require content that can take advantage of the display. In this paper, we propose a webized interactive CAD review system that uses super multi-view autostereoscopic displays with an application facilitating the popularization of super multi-view displays. The content for the display is described by web technologies such as HTML5, CSS, and JavaScript. The proposed system renders the content through a web browser and handles user interactions via JavaScript. A user can view autostereoscopic images with a sense of depth through motion parallax using the display and control the content remotely using gesture interaction devices. We present an example of content using a prototype implementation to verify our approach’s usefulness. © Springer International Publishing AG 2017.

关键词： Display devices

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Webizing virtual reality-based interactive interior design system 19th

Webizing virtual reality-based interactive interior design s...

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19th International Conference on Human-computer Interaction, HCI International 2017

作者： Seo, Daeil Lee, Jongho Yoo, Byounghyun Center for Imaging Media Research Korea Institute of Science and Technology Seoul Korea Republic of Department of Computer Science and Engineering Seoul National University of Science and Technology Seoul Korea Republic of Department of HCI and Robotics University of Science and Technology Daejeon Korea Republic of

ISBN: (纸本)9783319587523

The virtual reality (VR)-based interior design systems have the advantage of cost reductions and can support multiple users without spatial or temporal constraints. Recently, various head-mounted display (HMD) applications for VR using smartphones have become popular, and WebVR technology has been introduced to implement VR applications on the web. However, WebVR is still its early stages for use in the development of VR applications. Interaction methods for WebVR are limited compared to traditional VR development environments. In this paper, we propose an interactive VR system for interior design based on web technologies with a system that supports 3D and VR views with various interaction methods on the web. © Springer International Publishing AG 2017.

关键词： Virtual reality

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