Special Issue Proposal for Machine Vision and Applications (Springer) Special Issue on Intelligent Urban Computing with Big Data 1. Summary and Scope The rapid proliferation of urbanization has modernized many people’s lives, and also engendered critical issues, such as traffic congestion, energy consumption, and environmental pollution. These urbanization challenges seriously deteriorate people’s life quality in big cities. Nowadays, sensing technologies and large-scale computing infrastructures have produced a variety of big data in urban spaces, which provide rich knowledge about a city to help tackle these challenges. Consequently, the intelligent urban computing, which holistically exploits the big data in big cities to improve the urban environment, human life quality, and city operation systems, attacks massive attention in research and industrial fields. Many efforts have been dedicated to connect unobtrusive and ubiquitous sensing technologies, advanced data management and analytics models, and novel visualization methods to structure intelligent urban computing systems for smart cities. Furthermore, the intelligent systems and applications are emerging and becoming pervasive in the field of urban planning, transportation systems, environmental conservation, energy consumption, social applications, economy, public security, and presenting representative scenarios. The goal of this special issue is to call for a coordinated effort to understand the opportunities and challenges emerging in intelligent urban computing with big data, identify key tasks and evaluate the state of the art, showcase innovative methodologies and ideas, introduce interesting real-world intelligent urban computing systems or applications, as well as propose new real-world datasets and discuss future directions. We solicit original contributions in all fields of intelligent urban computing that explore the big data in big cities to help us understand the nature of urban phenomena and even predict the future of cities. We believe the special issue will offer a timely collection of research updates to benefit the researchers and practitioners working in the broad cloud computing and intelligence systems communities. To this end, we solicit original research and survey papers addressing the topics listed below (but not limited to): Machine vision based applications in smart city Intelligent systems and technology for urban sensing and city dynamics sensing Intelligent video surveillance or video sensor network Intelligent traffic system Public safety and security empowered by big visual data Mining data from the internet-of-things/sensor networks in urban areas Intelligent urban/multimedia computing using deep learning techniques Intelligent social computing with big visual data 2. Submission Guideline Authors should prepare their manuscripts according to the online submission page of Machine Vision and Applications at http://link.springer.com/journal/138. All the papers will be peer- reviewed following the Machine Vision and Applications reviewing procedures. The submissions should clearly demonstrate the evidence of benefits to society or large communities. Originality and impact on society, in combination with the media nature and innovative technical aspects of the proposed solutions will be the major evaluation criteria. 3. Tentative Deadlines Paper submission: September 30, 2016 First round notification: January 15, 2017 Revised Manuscript： March 31, 2017 Notification of Acceptance: June 15, 2017 Publication: Third Quarter of 2017 4. Guest Editors Dr. Wu Liu, Beijing University of Posts and Telecommunications, China Email: [email protected] Dr. Peng Cui, Tsinghua University, China Email: [email protected] Dr. Jukka K. Nurminen, Aalto University, Finland Email: [email protected] Dr. Jingdong Wang, Microsoft Research, China Email: [email protected] Dr. Wu Liu, Beijing University of Posts and Telecommunications, China Short Wu Liu is an Assistant Professor in Beijing University of Posts and Telecommunications, Bio: China. He received his PhD degree from Institute of Computing Technology (ICT), Chinese Academy of Science (CAS) in 2015. From Dec. 2014 to April. 2015, he was a visiting student in the University of Rochester, NY, USA. His current research interests include multimedia analysis and retrieval, and computer vision. In particular, he is interested in applying the techniques from these areas to a broad range of multimedia and vision applications, such as video analytics, multimedia search, intelligent video surveillance, and mobile applications. He has published more than ten papers in prestigious conferences and journals in computer vision and multimedia, including IEEE CVPR, ACM MM, ECCV, ICASSP, IEEE T-MM, IEEE T-CYB etc. His recent research won the 2016 CAS Outstanding Ph.D. Thesis Award, Chinese National Scholarship, Dean’s Special Award of CAS, Director of Special Award in ICT&CAS, “Baidu” HACKATHON 1st Prize, etc. Personal Webpage: http://liuwu.weebly.com/ Dr. Peng Cui, Tsinghua University, Beijing, China Short Peng Cui is now an Assistant Professor in Tsinghua University, China. He received his Bio: PhD degree from Tsinghua University in 2010. He is an active researcher dedicated to novel algorithms and systems in social multimedia computing, and he is keen to promote the convergence of social media data mining and multimedia computing technologies. Dr. Cui has strong backgrounds in both data mining and multimedia communities. He has published more than 30 papers in prestigious conferences and journals in data mining and multimedia, including ACM MM, SIGKDD, SIGIR, AAAI, IEEE TMM, IEEE TKDE, IEEE TIP etc. His recent research won the ACM MM12 Grand Challenge Multimodal Award, and MMM13 Best Paper Award. He is the Area Chair of ACM MM 2014, ICASSP 2013, Associate Editor of Frontier of Computer Science journal, Guest Editor of Information Retrieval journal, and co-organized several special sessions and workshops on social multimedia in ICMR, ICME, ACM MM and WSDM. Personal Webpage: http://media.cs.tsinghua.edu.cn/~multimedia/cuipeng/ Dr. Jukka K. Nurminen, Aalto University, Aalto, Finland Short Jukka K. Nurminen started as professor of computer science at Aalto University at the Bio: beginning of 2011. He has a strong industry background with almost 25 years’ experience of software research at Nokia Research Center. Jukka’s experience ranges from mathematical modeling to expert systems, from network planning tools to solutions for mobile phones, and from R&D project management to tens of patented inventions. Jukka received his M.Sc degree in 1986 and Ph.D. degree in 2003 from Helsinki University of Technology. Dr. Nurminen has published over 100 publications in scientific journals and conferences with around 1500 citations and Google h-index 21. He also applied 35 patent applications on the area of mobile applications and solutions. He is the board of directors of Finnish Operations Research Society, responsible professor of EIT Digital Master’s program on Cloud Computing and Services at Aalto, member of SCI School Advisory Board for Internationalization, member of the CCIS degree program committee, deputy member of Aalto DigiPlatform board of directors, responsible professor of Eurecom-Aalto SCI school cooperation, Co-chair of the “Video delivery over mobile networks: solutions and performance evaluation” workshop at WiOpt 2013&2014 conference, and Scientific director of the EIT ICT Labs Cloud Computing Summer School in 2012&2013. Personal Webpage: http://cse.aalto.fi/en/personnel/jukka-k-nurminen/ Dr. Jingdong Wang, Microsoft Research, China Short Jingdong Wang is a Lead Researcher at the Visual Computing Group, Microsoft Bio: Research Asia. He received the M.Eng. and B.Eng. degrees in Automation from the Department of Automation, Tsinghua University, Beijing, China, in 2001 and 2004, respectively, and the PhD degree in Computer Science from the Department of Computer Science and Engineering, the Hong Kong University of Science and Technology, Hong Kong, in 2007. His areas of interest include machine learning, pattern recognition, multimedia computing, and computer vision. In particular, he has worked on kernel methods, semi-supervised learning, data clustering, image segmentation, and image and video presentation, management and search. At present, he is mainly working on the Big Media project, including large-scale indexing and clustering, and Web image search and mining. Personal Webpage: http://research.microsoft.com/en-us/um/people/jingdw/ 5. Tentative Reviewers and Authors List The potential reviewers and possible authors can be: Name Email Organization Country Kingdom Adnan Shahid [email protected] Taif University of Saudi Arabia Ahmad Rezaee [email protected] Putrajay Universiti Putra Malaysia Jordehi m a Alvaro Rocha [email protected] University of Coimbra Portugal Amirhossein [email protected] Michigan State University USA Gandomi Bernardi United [email protected] Sheffield Hallam University Pranggono Kingdom Changjun Jiang [email protected] Donghua University China Institute of Automation, Chengqing Zong [email protected] China Chinese Academy of Sciences Jiangxi University of Finance Chengying Mao [email protected] China and Economics Chunming Hu [email protected] Beihang University China Dimitrios National Technical University of [email protected] Greece Stratogiannis Athens Enrico Masala [email protected] Politecnico di Torino Italy Esa Hyytia [email protected] University