题 目：Semantic Multimedia Content Analysis and Understanding
报告人：Prof. Jinchang Ren, University of Strathclyde
时 间：2019年7月25日上午10：00
地 点：青岛校区N5楼315会议室
Abstract:
In this talk, summarized works in several interesting topics on semantic multimedia content analysis and understanding will be reported. These include semantic video content analysis, image analysis, fusion and recognition, motion estimation and image registration, content based video annotation, summarisation and retrieval, archive video restoration, visual surveillance and 3D vision as well as saliency detection. In addition to the reported progress, intensive discussions on future R&D will be focused.
Short Biography:
Jinchang Ren is currently a Reader with the Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, UK. He received B. Eng. in Computer Software, M.Eng. in Image Processing and Pattern Recognition and EngD in Computer Vision from Northwestern Polytechnical University (NWPU), China, in 1992, 1997 and 2000, respectively. He was also awarded the PhD degree in Electronic Imaging and Media Communication from the University of Bradford, United Kingdom in 2009. Before he joined Strathclyde in Dec. 2010, he had worked in several universities in U.K. including University of Bradford, University of Surrey, Kingston University and University of Abertay, Dundee.
Dr. Ren has published over 260 peer-reviewed research papers in prestigious international journals and conferences, including over 150 in journals (100+ SCI cited). He is a Senior Member of IEEE, and a Fellow of the Higher Education Academy, U.K. His research interests include: image processing and analysis, intelligent multimedia information processing; visual computing; computer vision; content-based image/video retrieval and understanding; machine learning, big data analytics, visual surveillance; motion estimation; hyperspectral imaging. He sits in the editorial board of six int. journals, including J. The Franklin Institute, IEEE JSTARS, IET Image Processing, and Big Data Analytics et al.
