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Jinxiang joined Texas
A&M University in August 2006 as an assistant professor in Department
of Computer Science and Engieering. He received his Ph.D in 2006 from the
Robotics Institute at
Carnegie Mellon. His primary research is in the
area of computer graphics and animation with broad applications in other
disciplines such as computer vision, robotics, human computer
interaction, and biomechanics. He is particularly interested in
developing representations and efficient computational models that allow
acquisition, analysis, understanding, simulation, and control of natural
human movements. He draws on ideas from graphics, vision, machine
learning, robotics, biomechanics, psychology and applied math. He
recently received an NSF CAREER award for his work on theory and practice
of Bayesian motion synthesis.
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Two papers will be
presented at SIGGRAPH 2011: Leveraging Motion Capture and 3D
Scanning for High-fidelity Facial Performance Acquisition and Physically-Valid Statistical Models
for Human Motion Synthesis.
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Two
new NSF projects working on Theory and Practice of Bayesian Motion
Synthesis and Contact-Based
Human Motion Acquisition and Synthesis.
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I
am a program co-chair of CASA 2011, which will be held in Chengdu (成都),
one of the most beautiful cities in China.
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RESEARCH PROJECTS AND INTERESTS:
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Human motion analysis,
understanding and animation. The primary goals of our
research herein are: (1) to develop efficient representations and
computational models to analyze how humans move by utilizing prerecorded
motion data, physics, biomechanics principles, and control theories; and
(2) to apply the new models to solving important and challenging problems
in computer graphics such as synthesis and control of animated human
characters, performance animation, motion capture, motion planning, and
motion data processing.
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Motion capture for everyone. We are developing
next-generation motion capture technologies that minimize the cost and
intrusiveness of motion capture so that the technology is practical and easily
accessible to every home user. Two notable examples are performance
animation using low-cost sensors and video-based motion capture. We are
also interested in developing new techniques for capturing the physics of
complex movements from real world.
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Facial acquisition and animation. One
of holy grail problems in computer graphics has been the realistic
animation of the human face. We have been developing new methods to
animate and control virtual faces by capturing and analyzing facial
performances of real people.
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Visual modeling and understanding. We
seek to build systems that can visually model and understand complex
movements such as full-body movements, facial deformations, hand
gestures, multi-actor interaction, or animal movements. For example, we
have developed new techniques for modeling deformable objects and
articulated bodies from monocular image sequences. Before that, I had
been working on image-based modeling and rendering.
Data-driven graphics and vision. I
am genuinely interested in data-driven approaches for solving ill-posed
graphics and vision problems, such as animation control, deformation
modeling, vision-based motion tracking, and super-resolution. I am
particularly interested in learning techniques that can scale up to
massive and heterogeneous datasets.
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CSCE 643 (Spring
2012): Computer Vision
CSCE
181 (Fall 2011): Introduction to
Computing
CSCE
641 (Fall
2011): Computer Graphics
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SELECTED RECENT
PUBLICATIONS: (For
more details, see my Projects
page)
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Program Co-chair - Computer
Animation and Social Agents (CASA), 2011
Program committee - ACM SIGGRAPH ASIA, 2012, 2011, 2009
Program committee - Symposium on Computer Animation (SCA),
2012, 2011, 2010, 2009, 2008
Program committee -
ACM Symposium on Interactive 3D Graphics and Games
(I3D), 2012, 2011
Program committee - Pacific Graphics, 2012, 2011, 2010
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