In multimedia sensor networks, the multimedia sensors in the form of various cameras and recorders collect multimedia information including images, video and audio, which generate a large volume of heterogeneous data every day. How to represent, analyze and understand these multimedia sensor contributed data efficiently and effectively become a timely and important topic for both industry and academia.
Recent advancements in big data analytics have already opened many avenues for multimedia sensor networks related applications. Examples span a wide range of visual and audio understanding tasks including object/action recognition, speech recognition, multimedia search, machine translation, video event detection, vision to language, etc. There is no doubt that big data analytics will still contribute to these applications as well as other emerging multimedia sensor networks related applications. Therefore, more innovative methods and systems are highly desired to enrich the methodology and applications of both big data analytics and multimedia sensor networks.
This workshop is intended to provide a forum for researchers and engineers to present their latest innovations and share their experiences on all aspects of big data analytics in multimedia sensor networks. Topics of interest include, but are not limited to:
Wu Liu is currently a lecturer in Beijing Key Lab of Intelligent Telecommunications Software and Multimedia, Beijing University of Post and Telecommunications. He received the B.E. degree from Shandong University, Shandong, China, in 2009, and Ph.D. degree in computer application technology at the Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China. His research interests include multimedia information retrieval and computer vision. He received Chinese Academy of Sciences Outstanding Ph.D. Thesis Award in 2016, Best Student Paper Awards at ICME in 2016, Best Paper Runner-Up Awards at BIGCOM in 2016, and the Dean's Special Award of Chinese Academy of Sciences in 2015.
Lei Huang is now an associate professor with the Ocean University of China, Qingdao, China. He received the Ph.D. degree in computer science from the Institute of Computing Technology, Chinese Academy of Sciences, Beijing, in 2011. His current research interests are in the fields of multimedia content analysis and retrieval, image processing, pattern recognition and machine learning. He has published 15 papers in international journals and conferences including ACM Multimedia, ICIP, MMM, etc.
Zhineng Chen is now an associate professor with the Institute of Automation, Chinese Academy of Sciences, Beijing, China. He received his B.S. and M.S. degrees in computer science from the College of Information Engineering, Xiangtan University, China, in 2004 and 2007, respectively, and the Ph.D. degree in computer science from the Institute of Computing Technology, Chinese Academy of Sciences, Beijing, in 2011. He was a senior research associate with the Department of Computer Science, City University of Hong Kong, in 2012, and was an assistant professor with the Institute of Automation, Chinese Academy of Sciences, Beijing, from 2012 to 2014. His research interests include large-scale multimedia information retrieval, machine vision and pattern recognition. He has published more than 20 papers in prestigious multimedia and related conferences including ACM Multimedia, ICMR, MMM, etc.
Jianquan Ouyang is now a professor with Xiangtan University. He received the B.S. and M.A degree in computer science from Xiangtan University, China, in 1995 and 2001, respectively. Ph.D degrees in computer science from Institute of Computing Technology, Chinese Academy of Sciences, China in 2005. 2006-2009, he experienced on a postdoctoral project in School of Computer, National University of Defense Technology, China. Since 2000, he has been a faculty member at the Xiangtan University of China. His research interests include video analysis and retrieval. He has published more than 30 papers in prestigious multimedia journals and related conferences including Journal of Visual Communication and Image Representation, Plos One, etc.
Consistent with standard practice, each submitted manuscript will undergo rigorous peer reviewing by at least three qualified referees. Papers will be selected based on their originality, timeliness, significance, relevance, technical contents, and clarity of presentation.