Modeling Multimedia Behaviors
Multimedia analytics and modeling have already opened many research areas and spurred on tremendous amount of development on algorithms and applications which focus on analyzing large scale unstructured multimedia collections. While the modeling of multimedia ITSELF, such as the compression, transmission, content mining and retrieval, security and privacy, is of great importance—especially in the era of big data, when data volume is increasing exponentially—the human behaviors related to the generation, consumption, interaction and sharing of multimedia are still not well addressed. This is especially crucial with the ubiquitous adoption of smartphones and light-weight wearable devices which are equipped with multimedia sensing capabilities. These capabilities make it more feasible to characterize human behaviors, digitally, visually and semantically. In addition, the mobile Internet accessing infrastructure such as WiFi hotspots, 3G and 4G network facilitates the interaction with multimedia everywhere. We believe a full investigation on the modeling of multimedia behaviors will definitely benefit the end users in many aspects such as health care, urban planning, efficiency of digital resources usage, advertisement, etc.
This special session focuses on the most recent progress on modeling multimedia behavior from various aspects of human factors, such as interacting with multimedia contents, human behavior detection and recognition, behavioral mining and prediction, multimedia content distribution and streaming, etc. Novel applications or systems utilizing the modeling of multimedia behavior models are also welcomed.
Topics of Interest
The special session seeks original contribution of work, which addresses the challenges from, but not limited to, the following topics:
- Behavior tracking/monitoring using multimedia
- Interfaces & interaction with multimedia
- Multimedia sharing/streaming based on behavior models
- Behavior mining from mobile multimedia
- Long-term behavior storage and pattern mining
- QoE in multimedia systems
- Real-world use cases of behavior modeling
- Behavior data security and privacy issues
- Quantified Self/Lifelogging
- Systems, applications, services and implementations of multimedia behavior modeling
Peng Wang, Tsinghua University, China
Peng Wang is now a postdoctoral researcher in Department of Computer Science and Technology, Tsinghua University. He received his PhD degree in Computing from CLARITY: Centre for Sensor Web Technologies, Dublin City University on the topic of semantic mining and enhancement of lifelogging events. During 2010, he visited the Digital Enterprise Research Institute (DERI), National University of Ireland, Galway to work on applying Semantic Web technologies to the application of topic-related concept selection and semantic event enhancement. Since 2014, he has worked as a post doctor at the Department of Computer Science and Technology, Tsinghua University, Beijing, China. His current research interests include human behavior analysis, semantic mining from multimedia. He has published more than 20 peer-reviewed papers in journals, conferences and workshops, mainly on the topic of multimedia content analysis, event detection and recognition, human behavior mining from large scale mobilities, etc.
Frank Hopfgartner, University of Glasgow, Scotland
Frank Hopfgartner is a lecturer at University of Glasgow. His research to date can be placed in the intersection of interactive information retrieval, recommender systems, and multimedia content access. More recently, he focused on the application of game principles to incentivize users of information systems, also referred to as gamification. He (co-)authored over 100 publications in above mentioned research fields, including a book on smart information systems, various book chapters and papers in peer-reviewed journals, conferences and workshops. He served as Demo Co-Chair of MMM’12 and MMM’17, Special Session Co-Chair of MMM’14 as well as Proceedings Co-Chair of ICMR’14.
Liang Bai, National University of Defense Technology, China
Liang Bai is currently an associate professor in the School of Information System and Management, National University of Defense Technology. He received the B.E. (Bachelor Degree of Engineering) and B.M. (Bachelor Degree of Management) degrees in 2002 from Xi’an Jiao Tong University, and M.E. degree in 2005, Ph.D. degree in 2008 both from National University of Defense Technology. He has published about 60 peer-reviewed papers. He is also a regularly reviewer for a number of top international or Chinese journals. He was awarded the Second Prize for Science and Technology Development of the Ministry of Education, P.R. China in 2011. His research interest includes multimedia content analysis and access, particularly for video and image. Big Multimedia Data is also his research focus now. He is a member of ACM and IEEE Computer Society, and a member of the Chinese Computer Society.