点云压缩:应用和挑战
Point Cloud Compression: Applications and Challenges
李竹   Zhu Li
报告人照片   Zhu Li is an associated professor with the Dept of CSEE, University of Missouri, Kansas City, USA, directs the Multimedia Computing & Communication Lab and the new NSF I/UCRC Center for Big Learning at UMKC. His research interests include image/video analysis, compression, and communication and associated optimization and machine learning tools. He has 30+ issued or pending patents, 90+ publications in book chapters, journals, conference proceedings and standards contributions in these areas.
  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.
报告时间:2018年03月26日10时00分    报告地点:西区科技实验楼西1213
报名截止日期:2018年03月26日    可选人数:40