SeSaMe Seminar by Professor Liu Yanxi
Title: Human versus Machine Perception of Visual Regularity
Speaker: Professor Liu Yanxi
Date & Time: 1st August 2016 (Mon), 10.30am - 11.30am
Venue: Seminar Room 9, COM1 (#02-09)
Abstract: Regularities with varying form and scale pervade our natural and man-made world. From insects to mammals, the ability to sense regular patterns has a neurobiological basis and has been observed in many levels of intelligence and behavior. From Felix Kleins Erlanger program, D’Arcy Thompson’s Growth-and-Form, to the Gestalt principles of perception, much of our understanding of the world is based on the perception and recognition of repeated patterns, generalized by the mathematical concept of symmetry and symmetry groups. Given the ubiquity of symmetry in both the physical and the digital worlds, a computational model for symmetry-based regularity perception is especially pertinent to computer vision, computer graphics, robotics and machine intelligence in general, where an intelligent being (e.g. a robot) seeks to perceive, reason and interact with the chaotic world in the most effective and efficient manner. Surprisingly, we have limited knowledge on how humans perceive regular patterns and little progress has been made in computational models for noisy, albeit near-regular patterns in real data. In this talk, I present parallels as well as differences between machine perception and human perception of visual regularity. I shall report our recent results on understanding human perception of wallpaper patterns using neuroimaging (EEG, fMRI) and crowdsourcing, and our successful attempt at building a symmetry-based Turing test to tell humans and robots apart: a symmetry reCAPTCHA.
Bio: Yanxi Liu received her B.S. degree in physics/electrical engineering (Beijing, China), her Ph.D. degree in computer science on group theory applications in robotics (University of Massachusetts, Amherst, US), and her postdoctoral training in the robotics lab of LIFIA/IMAG (Grenoble, France). Before joining the faculty of the Robotics Institute of Carnegie Mellon Institute in 1996 she spent one year at DIMACS (NSF center for DIscrete MAthematics and Theoretical Computer Science) under an NSF research-education fellowship award. Currently, Dr. Liu is a full professor with the School of Electrical Engineering and Computer Science at Penn State University, where she co-directs the lab for perception, action and cognition (LPAC), and the Human Motion Lab for Taiji (Tai Chi) Research. Dr. Liu's research interests span a wide range of applications including computer vision, computer graphics, robotics, human perception and computer aided diagnosis in medicine, with one central theme: computational regularity. She is the leading author of a 200-page survey (book by NOW) on “Computational Symmetry in Computer Vision and Computer Graphics”, and her 2013-2014 visit to Microsoft Silicon Valley and Google Mountain View resulted in two granted patents on applications of computational symmetry. Currently, Dr. Liu serves as an associate editor for IEEE Transaction of Pattern Analysis and Machine Intelligence (PAMI) and an area editor for Journal of Computer Vision and Image Understanding (CVIU). She will be the program co-chair for the 2017 CVF/IEEE Computer Vision and Pattern Recognition (CVPR) Conference.