报告题目：Cascaded face alignment via intimacy definition feature
报告时间：2018年6月4日（周一）下午，4:00-5:00
报告地点：信息学院12教703
报告专家：香港理工大学 Prof. Kenneth K.M. Lam
报告内容简介：Recent years have witnessed the emerging popularity of regression-based face aligners, which directly learn mappings between facial appearance and shape-increment manifolds. In this talk, he will introduce a random-forest-based, cascaded regression model for face alignment by using a novel locally lightweight feature, namely intimacy definition feature (IDF).
报告人简介：Prof. Kenneth K.M. Lam received his Associateship in Electronic Engineering from the Hong Kong Polytechnic University in 1986. In August 1993, he undertook a Ph.D. degree program in the Department of Electrical Engineering at the University of Sydney, Australia. He completed his Ph.D. studies in August 1996. Prof. Lam was the Director-Student Services and the Director-Membership Services of the IEEE Signal Processing Society between 2012 and 2014, and between 2015 and 2017, respectively. He was an Associate Editor of IEEE Trans. on Image Processing between 2009 and 2014, and an Area Editor of the IEEE Signal Processing Magazine between 2015 and 2017. Prof. Lam serves as an Associate Editor of Digital Signal Processing, APSIPA Trans. on Signal and Information Processing, and EURASIP International Journal on Image and Video Processing. He is also an Editor of HKIE Transactions. His current research interests include human face recognition, image and video processing, and computer vision.
