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题目： Just-Noticeable Difference (JND) Formulation for Signals and Beyond
报告人： Professor Weisi Lin（School of Computer Engineering, Nanyang Technological University, Singapore）
时间： 2016年3月25日（星期五），上午10:00 – 11:00
邀请人： 王瀚漓 教授
Weisi Lin obtained his BSc and MSc from Sun Yat-Sen University, Guangzhou, and PhD from King’s College, London University, and is an active researcher in image processing, video compression, quality metrics and perceptual modeling of visual signals, and multimedia communication. He served as the head of the Visual Processing Lab and the Acting Manager of the Media Processing Department in Institute for Infocomm Research (I2R), Singapore. He is currently an Associate Professor, School of Computer Engineering, Nanyang Technological University. He published 150 international journal papers, 220+ conference papers, 2 authored books, 3 edited books, 9 book chapters and 7 patents, and successfully delivered R&D projects with $6m funding as the PI. He has been elected as a Distinguished Lecturer for IEEE Circuits and Systems Society (2016-2017), and Asia-Pacific Signal and Information Processing Association (2012-13), and given keynote/invited/tutorial/panel talks to over 20 international conferences. He is an AE for IEEE Trans. on Image Processing, IEEE Trans. Circuits and Systems for Video Technology, IEEE Signal Processing Letters and Journal of Visual Communication and Image Representation, and a past AE for IEEE Trans. on Multimedia. He has been elected as a Fellow of IEEE and IET. He believes that good theory is practical, and has kept a balance of academic research and industrial deployment (and business development) throughout his working life.
As a result of the evolution, the human has developed unique characteristics in perception of viewing, hearing, smelling, touching and tasting. Just Noticeable Difference (JND) refers to the minimal amount of “X” that must be changed for the difference to be sensed by the human, where X can be any signal, derived quantity from signals such as emotion and user-experience, or even technical specifications such as resolution, asynchrony, accuracy, etc. “Perception is reality”, so JND plays an important role both explicitly and implicitly throughout our work and life, from sound to smell and from engineering to marketing (e.g., advertisement, logo management, personalization, and recommendation). The scientific measurement and formulation for JND are the prerequisite for user-centric designs and for turning human perceptual sensitivities into many system advantages. In this talk, a holistic view will be first presented on JND research and practice, followed by an in-depth case study in visual signals. JND modeling for visual signals has attracted much research interests so far, while those for audio, haptics, olfaction, gestation and other forms of signals are expected to intensify. In essence, factors to influence JND also include utility, culture and personality, as to be highlighted.