特邀嘉宾：刘永怀 教授（英国边山大学）
报告时间：2022年05月24日（周二） 16：00-17:30
腾讯会议：163-463-116
报告摘要：3D data can be obtained relatively easily nowadays through many ways. In this talk, I will firstly outline the main methods for 3D data acquisition, then discuss the main issues for saliency analysis and detection, and their potential applications. A novel unsupervised multi-view CNN (UMVCNN) will thirdly be proposed for the task of saliency detection, based on the universal principle “View-Object Consistency”. Some experimental results will be shown to demonstrate the performance of the proposed UMVCNN method for two fundamental but challenging tasks for 3D data analysis, best view selection and interest point detection. I will finally conclude the talk with few observations, followed by a brief discussion of the future work.
报告人简介：Dr Yonghuai Liu is a professor and director of the Visual Computing Lab at Edge Hill University since 2018. He obtained his first PhD degree in 1997 from Northwestern Polytechnical University, P.R. China and second PhD degree in 2001 from The University of Hull, United Kingdom. He previously worked at Aberystwyth University as a senior lecturer since 2011 and as a lecturer since 2001. He is currently an area/associate editor or editorial board member for a number of international journals and conference proceedings, including Pattern Recognition Letters, Neurocomputing, American Journal of Educational Research, and Proceedings of IEEE International Conference on Robotics and Automation. He is also a guest editor for a number of international journals, including International Journal of Computer Vision. He has been serving as programme committee member and referee for more than 90 international conferences and journals. He won a number of international awards as the best editor, and the best reviewer from the top-ranked international conferences in the field. He has published more than 190 papers in the top-ranked international conference proceedings and journals. His primary research interests lie in 3D computer vision, image processing, pattern recognition, machine learning, artificial intelligence, and intelligent systems. He is a senior member of IEEE, Fellow of British Computer Society and Fellow of Higher Education Academy of United Kingdom.