11月10日学术报告信息（Kodak Alaris Inc.Alexander C. Loui）
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报告题目：Event-based Framework for Intelligent Management of Personal Media
报告日期及时间：2015年11月10日周二10：00-11：00
报告地点： 重点实验室E202
报告人： Alexander C. Loui
报告人单位：Kodak Alaris Inc.
 
报告人简介：Alexander C. Loui obtained his B.A.Sc. (Honors), M.A.Sc, and Ph.D. all in Electrical Engineering from the University of Toronto, Canada. After completing his Ph.D. in 1990, he joined Bellcore in New Jersey as a Member of Technical Staff working on audiovisual compression, multipoint video conferencing, and video-on-demand technologies. From 1996-2013, he was with Kodak Research Labs in Rochester NY as a Principal Scientist in the Image Science Division and later a Principal Investigator at the Computational Science and Technology Lab. He is currently a Senior Principal Scientist and Technical Lead at Kodak Alaris (a spin-off company from Kodak). Dr. Loui has been directing research on multimedia processing and content recognition, video analysis and summarization, digital image management, event detection, image quality assessment, and machine vision applications. He has published over 90 refereed papers in these areas. He is also an Adjunct Professor of the ECE Department at Ryerson University and University of Toronto.
Dr. Loui was Chair (2010-11) of the IEEE Rochester Section, and Chair (2005) of the Rochester Chapter of IEEE Signal Processing Society. Dr. Loui has received a number of awards from Kodak and the R&D community for innovative research on auto-albuming and image management technologies. He is a Kodak Distinguished Inventor (with over 70 granted US patents) and a Fellow of IEEE and SPIE.

报告摘要： With the ubiquitous presence of mobile devices and smartphone cameras, people capture large numbers of images and videos to mark both events that are important to them, as well as day-to-day occurrences that chronicle their lives. These multimedia assets are being stored on various locations including social networks, mobile devices, cloud-based storages, and local PCs/hard drives. The large collections of distributed personal and social media assets make it increasingly difficult for users to retrieve specific images or videos from an event or to select specific scenes for creating a photobook or multimedia story for sharing. In this seminar, I will highlight research activities on intelligent asset management using a framework of event-based algorithms. Event detection and classification approaches using machine learning techniques are described. I will review an event-based feature representation for classifying events comprising of both images and videos into different semantic categories. I will present some recent work on detecting thematic recurring events using pattern mining of large image collections. If time permits, I will also describe the use of time-series analysis for detecting significant events. The proposed framework provides a coherent and integrated approach for efficient organization of personal media assets..
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