*VSE Seminar: Decomposition, Approximation and Reconstruction of Large 
Geometric Data*
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*Jyh-Ming Lien*
Assistant Professor, Department of Computer Science, GMU

Wednesday, Oct 31
10:30 - 11:30 AM
Research Hall, Room 163

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*Abstract:*
Complex geometric data comprising millions to billions of elements 
are omnipresent in variety of domains. Examples include point clouds 
of urban landscapes, polygon soup representing buildings in major 
cities, and combinatorial data structures induced from the motion of a 
robot. The unstructured nature of the data and significant amount of 
noise pose grand challenges in designing efficient and practical 
geometric algorithms.

In this talk, I will provide an overview of these challenges 
and algorithmic solutions developed by me and my students 
for representing, and manipulating massive geometric data of shape 
and motion. In particular, I will focus the discussion on two of our 
main contributions: (1) approximate representations via decomposition 
and (2) robust mesh reconstruction and repair. I will also discuss 
their applications in the areas of CAD, GIS, and robotics. Our 
research results have attracted a wide range of interests from 
academia, open-source software communities and industry.

*Bio:*
Jyh-Ming Lien is an Assistant Professor in the Department of 
Computer Science. He directs the Motion and Shape Computing (MASC) group 
and is affiliated with the Autonomous Robotics Laboratory at George 
Mason University. He received his Ph.D. in Computer Science from Texas 
A&M University in 2006. Prior to joining George Mason in 2007, he was 
a postdoctoral researcher at UC Berkeley. His recent work focuses 
on shape decomposition, approximation and reconstruction of complex 
and dynamic 3D geometries. His research has been supported by NSF, 
USGS, DOT, AFOSR, and Virginia Center for Innovative Technology. 
More images, videos, papers, and software about his work can be found 
at: https://masc.cs.gmu.edu/