▷ Place: GSCT 윤이상홀(N2, #102)
▷ Speaker: prof. Cyrus Shahabi (Director), Dr. Seon Ho Kim, Ugur Demiryurek
An Introduction to USC Integrated Media Systems Center (IMSC)
In this talk, I introduce the vision, research and projects of the Integrated Media Systems Center (IMSC), a graduated NSF Engineering Research Center at USC in the area of multimedia. The current research focus of IMSC is on a new geo-socio-temporal computing paradigm, termed Geo-Immersion. Geo-Immersion enables humans to capture, model and integrate real-world data into a geo-realistic virtual replica of the world for immersive data access, querying and analysis. It encompasses research in many interesting topics such as multimedia, participatory-sensing, privacy, trust, web, geospatial and temporal data management, etc. But more importantly, it brings up new fundamental research challenges in computer and social sciences to study the fusion of human behaviors in the real and virtual worlds.
Cyrus Shahabi is a Professor of Computer Science and Electrical Engineering and the Director of the Information Laboratory (InfoLAB) at the Computer Science Department and also the Director of the NSF's Integrated Media Systems Center (IMSC) at the University of Southern California. He is also the CTO and co-founder of a USC spin-off, Geosemble Technologies. He received his B.S. in Computer Engineering from Sharif University of Technology in 1989 and then his M.S. and Ph.D. Degrees in Computer Science from the University of Southern California in May 1993 and August 1996, respectively. He authored two books and more than two hundred research papers in the areas of databases, GIS and multimedia. Dr. Shahabi has received funding from several agencies such as NSF, NIJ, NASA, NIH, DARPA, AFRL, and DHS as well as several industries such as Chevron, Google, Intel, Microsoft, NCR and NGC. He was an Associate Editor of IEEE Transactions on Parallel and Distributed Systems (TPDS) from 2004 to 2009. He is currently on the editorial board of the VLDB Journal, IEEE Transactions on Knowledge and Data Engineering (TKDE), ACM Computers in Entertainment and Journal of Spatial Information Science. He is the founding chair of IEEE NetDB workshop and also the general co-chair of ACM GIS 2007, 2008 and 2009. He chaired the nomination committee of ACM SIGSPATIAL for the 2011-2014 terms. He regularly serves on the program committee of major conferences such as VLDB, ACM SIGMOD, IEEE ICDE, ACM SIGKDD, and ACM Multimedia. Dr. Shahabi is a recipient of the ACM Distinguished Scientist award in 2009, the 2003 U.S. Presidential Early Career Awards for Scientists and Engineers (PECASE), the NSF CAREER award in 2002, and the 2001 Okawa Foundation Research Grant for Information and Telecommunications. He was the recipient of US Vietnam Education Foundation (VEF) faculty fellowship award in 2011, an organizer of the 2011 National Academy of Engineering “Japan-America Frontiers of Engineering” program, an invited speaker in the 2010 National Research Council (of the National Academies) Committee on New Research Directions for the National Geospatial-Intelligence Agency, and a participant in the 2005 National Academy of Engineering “Frontiers of Engineering” program.
Geovid: Geo-Tagged Mobile Video Management System
User generated video content is experiencing significant growth which is expected to continue and further accelerate. As an example, users are currently uploading 24 hours of video per minute to YouTube. Making such video archives effectively searchable is one of the most critical challenges of multimedia management. Current search techniques that utilize signal-level content extraction from video struggle to scale. Here we present a framework based on the complementary idea of acquiring sensor streams automatically in conjunction with video content. Of special interest are geographic properties of mobile videos. The meta-data from sensors can be used to model the coverage area of scenes as spatial objects such that videos can effectively, and on a large scale, be organized, indexed and searched based on their geographical properties. We present an overall framework that is augmented with our design and implementation ideas to illustrate the feasibility of this concept of managing geo-tagged video.
Dr. Seon Ho Kim is currently working as an Associate Director in the Integrated Media Systems Center (IMSC) at the University of Southern California. Before joining IMSC, he worked at the University of Denver and the University of the District of Columbia as faculty for eleven years. He received his BS degree in Electronic Engineering from the Yonsei University, Seoul, Korea in 1986. He also received his MS in Electrical Engineering and Ph.D. in Computer Science from the University of Southern California, California, in 1994 and 1999, respectively.
Dr. Kim's primary research interests include multimedia systems, databases, GIS, and mobile video data management, where he has more than 50 publications including a textbook, major journal papers, and top conference papers. He has been serving the research community as conference program committee member, journal editorial board member and reviewer.
TransDec: A Data-Driven Framework for Decision-Making in Transportation Systems
The vast amounts of transportation datasets, so-called big data, collected from the traffic sensors (e.g., loop detectors, cameras) are extremely valuable in both the real-time decision-making, planning, and management of the transportation systems as well as conducting research to develop new policies to enhance the efficacy of transportation infrastructures. In this talk, I will introduce our data-driven framework, dubbed TransDec (short for Transportation Decision-Making), which enables real-time integration, visualization, spatiotemporal querying, and analysis of dynamic and archived traffic sensor data. I will discuss inherent challenges in developing a scalable system that allows for efficient querying and analysis of both real-time and archived very large scale datasets. Subsequently, I will present a next-generation route planning algorithm in time-dependent road networks where the weights on the network edges are function of time due to the variability of traffic congestion.