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Point Cloud Compression and Communication
时间:2018-12-13 11:25    点击:   所属单位:电子工程学院
讲座名称 Point Cloud Compression and Communication
讲座时间 2018-12-21 10:00:00
讲座地点 西电北校区主楼III区201 会议室
讲座人 Prof. Zhu Li
讲座人介绍 Zhu Li is an associated professor with the Dept of CSEE, University of Missouri, Kansas City, USA, directs the new NSF I/UCRC Center for Big Learning at UMKC.  He received his PhD from Electrical & Computer Engineering from Northwestern University in 2004, and was AFRL Summer Visiting Faculty at the US Air Force Academy, UAV Research Center, 2016, 2017 and 2018, Sr. Staff Researcher/Sr. Manager with Samsung Research America's Multimedia Core Standards Research Lab in Dallas, from 2012-2015, Sr.Staff Researcher with FutureWei(Huawei)'s Media Lab in Bridgewater, NJ, from 2010-2012,  Assistant Professor with the Dept of Computing, The HongKong Polytechnic University from 2008 to 2010, and a Principal Staff Research Engineer with the Multimedia Research Lab (MRL), Motorola Labs, Schaumburg, Illinois, from 2000 to 2008. His  research  interests  include  image/video  analysis,   compression,   and  communication  and  associated optimization and machine learning tools. He has 46 issued or pending patents, 100+ publications in book chapters, journals, conference proceedings and standards contributions in these areas. He received a Best Paper Award from IEEE Int'l Conf on Multimedia & Expo (ICME) at Toronto, 2006, and a Best Paper Award from IEEE Int'l Conf on Image Processing (ICIP) at San Antonio, 2007.
讲座内容  Point cloud data arise from depth sensing and capturing for both navigation/smart city, as well as content capture and VR/AR playback applications. Recent advances in sensor technology and algorithms, especially high resolution structured light in conjunction with very high resolution RGB camera arrays, have made point cloud capture getting closer to real world applications. In this talk we will discuss the main technical challenges in point cloud compression, especially the static and dynamic geometry  compression,  as  well  as  attributes  compression  problems,  and  the  new  graph  signal processing tools that can bring new coding efficiency. Some initial results will be presented and discussed, as well as the upcoming MPEG Point Cloud Compression call for proposal and results.
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