讲座时间：2016年11月30日10:00

讲座地点：科研楼B539

讲座题目： Rate Agnostic Content Identification and De-duplication in the Multimedia Networks

主讲人： Zhu Li, Associate Professor, IEEE Senior Member, University of Missouri, Kansas City

报告简介：The Internet is now dominated by the video traffic, and efforts are underway to re-architect the next-gen Internet to better serve the video traffic, moving away from a connectivity-centric design, to a content-centric design. One central issue for this is a new compact and robust media content identification scheme that can enable efficient content discovery, routing, redundant elimination in the networks, and a fast, rate-agnostic content identification and de-duplication in various network caches. In this talk, I will present a Scaled Eigen Appearance Feature (SEAF) modeling scheme that has been demonstrated to be very effective in playback verification, and a SEAF indexing forest solution for approximate nearest frame search, with a highly efficient likelihood pruning scheme, can provide highly accurate and fast content fragments discovery and de-dupcliation in large video repository in caches.

主讲人简介：Zhu Li is now an Associate Professor with the Dept. of Computer Science & Electrical Engineering (CSEE), University of Missouri, Kansas City, and director of the Multimedia Computing & Communication (MC2) Lab. He received his PhD in Electrical & Computer Engineering from Northwestern University, Evanston in 2004. He is the ad-hoc group co-chair for the MPEG Point Cloud Compression group. He was AFRL Faculty Fellow at the US Air Force Academy in Summer 2016, Sr. Staff Researcher/Sr. Manager with Samsung Research America's Multimedia Standards Research Lab in Richardson, TX, 2012-2015, Sr. Staff Researcher/Media Analytics Group Lead with FutureWei (Huawei) Technology's Media Lab in Bridgewater, NJ, 2010~2012, and an Assistant Professor with the Dept. of Computing, The Hong Kong Polytechnic University from 2008 to 2010, and a Principal Staff Research Engineer with the Multimedia Research Lab (MRL), Motorola Labs, from 2000 to 2008.

His research interests include audio-visual analytics and machine learning with its application in large scale video repositories annotation, mining and recommendation, video object identification and event recognition, as well as video adaptation, source-channel coding and distributed optimization issues of the wireless video networks. He has 25 issued or pending patents, 90+ publications in book chapters, journals, conference proceedings and standard contributions in these areas. He is an IEEE senior member, Ad Hoc Co-Chair of the MPEG Point Cloud Compression group, associated editor (2015~) for IEEE Trans. on Multimedia, and associated editor (2016~) for IEEE Trans on Circuits & System for Video Technology, associated editor (2015~) for Journal of Signal Processing Systems (Springer), steering committee member of IEEE ICME, elected member (2014-2017, 2017-2020) of the IEEE Multimedia Signal Processing (MMSP) Tech Committee, elected Vice Chair (2008-2010), Standards Liaison (2014-2016) and Steering Committee Chair (2016-) of the IEEE Multimedia Communication Technical Committee (MMTC), member of the Best Paper Award Committee, ICME 2010, co-editor for the Springer-Verlag book on "Intelligent Video Communication: Techniques and Applications", and " Multimedia Analysis, Computing and Communication,". He received the Best Paper Award at IEEE Int'l Conf on Multimedia & Expo (ICME), Toronto, 2006, and the Best Paper (DoCoMo Labs Innovative Paper) Award at IEEE Int'l Conf. on Image Processing (ICIP), San Antonio, 2007.