Storing and Querying Video Data
The proliferation of inexpensive high-quality cameras coupled with recent advances in machine learning and computer vision have enabled new applications on video data. This in turn has renewed interest in video data management systems (VDMSs).
In this talk, we explore how to build a modern data management system for video data. We focus, in particular, on the storage manager and present several techniques to store video data in a way that accelerates queries over that data. We then move up the stack and discuss different types of data models that can be exposed to applications. Finally, we discuss how it's possible to support users in expressing queries to find events of interest in a video database.
Magdalena Balazinska is Professor, Bill & Melinda Gates Chair, and Director of the Paul G. Allen School of Computer Science & Engineering at the University of Washington. Magdalena's research interests are in the field of database management systems. An ACM Fellow, her current research focuses on data management for data science, big data systems, cloud computing, and image and video analytics. She received her Ph.D. from the Massachusetts Institute of Technology (MIT). Read more about Dr. Magdalena Balazinska at https://www.cs.washington.edu/people/faculty/magda.
TRIANGLE COMPUTER SCIENCE DISTINGUISHED LECTURER SERIES:
The computer science departments at Duke University, North Carolina State University, and the University of North Carolina at Chapel Hill joined forces to create the Triangle Computer Science Distinguished Lecturer Series. The lecture series began in the 1995-1996 academic year, and is made possible by grants from the U.S. Army Research Office, rotated between the departments.