Computational Symmetry

Speaker:	Dr. Yanxi LIU
		Computer Science Engineering
		Electrical Engineering
		Penn State University

Title:		"Computational Symmetry"

Date:		Thursday, 11 February 2010

Time:		2:00pm - 3:00pm

Venue:		Room 3311 (via lift 17/18), HKUST

Abstract:

Symmetry is an essential mathematical concept, as well as a ubiquitous,
observable phenomenon in nature, science and art. Either by evolution or
by design, symmetry implies an efficiency coding that makes it universally
appealing, especially so to computational science. Recognition and
categorization of symmetry and regularity is the first step towards
capturing the essential skeleton of a real world problem, while at the
same time minimizing computational redundancy. However, symmetry group
detection from real world data turns out to be a challenging problem that
has been puzzling computer vision, computer graphics and psychology
researchers for decades. We explore a formal and computational
characterization of real world regularity using a hierarchical model of
symmetry groups as a theoretical basis, embedded in a well-defined
Bayesian framework. Such a formalization simultaneously facilitates (1) a
robust and comprehensive algorithmic treatment of the whole regularity
spectrum, from regular (perfect symmetry), near-regular (approximate
symmetry), to various types of irregularities; (2) an effective detection
scheme for real world symmetries and symmetry groups; and (3) a set of
computational bases for measuring and discriminating quantified
regularities on diverse data sets. Besides some theoretical background on
crystallographic groups in particular, I shall illustrate various
applications of computational symmetry in texture synthesis, analysis,
tracking, and manipulation; human gait and activity recognition;
symmetry-based dance analysis; grid-cell clustering; automatic
geo-tagging; and image 'defencing'.

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Biography:

Yanxi Liu received her B.S. degree in physics/electrical engineering in
Beijing and her Ph.D. degree in computer science for group theory
applications in robotics from University of Massachusetts (Amherst). Her
postdoctoral training was at LIFIA/IMAG (France). She also spent one year
at DIMACS (NSF center for Discrete Mathematics and Theoretical Computer
Science) under an NSF research-education fellowship award. Dr. Liu was
with the research faculty in the Robotics Institute (RI) of Carnegie
Mellon University before she joined the Computer Science Engineering and
Electrical Engineering departments of Penn State University in Fall of
2006 as a tenured faculty and the co-director of the lab for perception,
action and cognition (LPAC). 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
two main themes: computational symmetry/regularity and discriminative
subspace learning. Dr. Liu chaired the First International Workshop on
Computer Vision for Biomedical Image Applications (CVBIA) in conjunction
with ICCV 2005. Dr. Liu served as an area chair or organizing committee
member for CVPR08/MICCAI08/CVPR09, and has served as a multi-year
chartered study section member for the US National Institute of Health
(NIH). Dr. Liu is a senior member of IEEE and the IEEE Computer Society.