Symposium on Perceptual Technologies

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Schedule

Time Monday, October 1st
13.30-14.00 hrs Prof. Albrecht Schmidt (Medieninformatik, LMU München, DE): Amplifying the Senses
14.00-14.30 hrs Dr. Lewis Chuang (Medieninformatik, LMU München, DE): Extending Cybernetics with Neuroergonomics
14.30-15.30 hrs Prof Weisi Lin (Electrical Engineering, Nanyang TU, SG): Formulate and Implement Human Visual Attention Models
15.30-15.35 hrs PD Dr. Zhuanghua Shi (Psychology, LMU München, DE): Personal Introduction
15.35-15.40 hrs Prof. Qing Xu (Tianjin University, CN): Personal Introduction
15.40-15.45 hrs Dr. Yuanting Liu (Fortiss GmbH): Personal Introduction
15.45-16.00 hrs Thomas Rottmann (Universität Bundeswehr München, DE): Vehicle-in-the-Loop Simulator
16.00-16.15 hrs Coffee Break
16.15-17.00 hrs Demos
17.15-17.45 hrs Roundtable Discussion
18.00-20.00 hrs Dinner at Paulaner Bräuhaus

Guest Keynote: Formulate and Implement Human Visual Attention Models

Prof. Weisi Lin
Nanyang Technological University, Singapore

Weisi Lin is an active researcher in image processing, perception-based signal modelling and assessment, video compression, and multimedia communication systems. In the said areas, he has published 210+ international journal papers and 240+ international conference papers, 7 patents, 9 book chapters, 2 authored books and 3 edited books, as well as excellent track record in leading and delivering more than 10 major funded projects (with over S$7m research funding). He earned his Ph.D from King’s College, University of London. He had been the Lab Head, Visual Processing, in Institute for Infocomm Research (I2R). He is a Professor in School of Computer Science and Engineering, Nanyang Technological University, where he served as the Associate Chair (Graduate Studies) in 2013-2014.

He is a Fellow of IEEE and IET, and an Honorary Fellow of Singapore Institute of Engineering Technologists. He has been elected as a Distinguished Lecturer in both IEEE Circuits and Systems Society (2016-17) and Asia-Pacific Signal and Information Processing Association (2012-13), and given keynote/invited/tutorial/panel talks to 20+ international conferences during the past 10 years.  He has been an Associate Editor for IEEE Trans. on Image Processing, IEEE Trans. on Circuits and Systems for Video Technology, IEEE Trans. on Multimedia, IEEE Signal Processing Letters, Quality and User Experience, and Journal of Visual Communication and Image Representation. He was also the Guest Editor for 7 special issues in international journals, and chaired the IEEE MMTC QoE Interest Group (2012-2014); he has been a Technical Program Chair for IEEE Int’l Conf. Multimedia and Expo (ICME 2013), International Workshop on Quality of Multimedia Experience (QoMEX 2014), International Packet Video Workshop (PV 2015), Pacific-Rim Conf. on Multimedia (PCM 2012) and IEEE Visual Communications and Image Processing (VCIP 2017). He believes that good theory is practical, and has delivered 10 major systems and modules for industrial deployment with the technology developed.

Abstract

As a result of human evolution, visual attention (VA) refers to the cognitive process of selectively concentrating on certain visual aspects in a scene that are most interesting (e.g., we pay more attention to a colorful flower among many green leaves in a picture), and has attracted continuousresearch effort since William James’ time.   It is beneficial to model VA computationally and incorporate an appropriate model in signal evaluation and processing, since the human is the final receiver and appreciator for most (if not all) processed signals, and the scarce system resource is better to be utilized in user-centric manners. In addition, there is an increasing need for harmonious human-machine interaction (imagining that robots act as caregivers of senior citizens, salespersons in a future shopping mall, and even colleagues in work places) and artificial intelligence (AI), and therefore it would be good if machines possess similar attention and selectivity mechanisms as humans.
In this talk, we will first introduce the research problems associated with VA, as well as the relevantphysiological and psychological ground.  Afterward, we are to discuss the principle of computational VA modelling and the advances in the area, including the bottom-up, top-down and combined approaches. Meaningful applications in perceptual quality assessment, image retargeting, video coding, computer graphics, and target identification, as well as the related industrial deployment,are then demonstrated. The talk will also present our opinions toward possible future research and development.