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OlgaTitle: Interactive mesh deformation with reality-inspired constraints

Abstract:
Irregular triangle meshes are a powerful digital shape representation:
they are flexible and can represent virtually any complex shape; they
are efficiently rendered by graphics hardware; they are the standard
output of 3D acquisition and routinely used as input to simulation
software. Yet irregular meshes are difficult to model and edit because
they lack a higher-level control mechanism. In this talk, I will
survey a series of research results on surface modeling via mesh
deformation and show how high-resolution meshes can be interactively
manipulated and animated in a fast and intuitive manner. I will also
discuss how the incorporation of some physics laws directly into the
interactive modeling framework can be done inexpensively and
beneficially for geometric modeling: while not being as restrictive
and parameter-heavy as a full-blown physical simulation, this allows
to creatively model shapes with improved realism and directly use them
in fabrication.


Bio:
Olga Sorkine-Hornung is an Assistant Professor of Computer Science at ETH Zurich, where she leads the Interactive Geometry Lab at the
Institute of Visual Computing. Prior to joining ETH she was an Assistant Professor at the Courant Institute of Mathematical Sciences,
New York University (2008-2011). She earned her BSc in Mathematics and Computer Science and PhD in Computer Science from Tel Aviv University (2000, 2006). Following her studies, she received the Alexander von Humboldt Foundation Fellowship and spent two years as a postdoc at the Technical University of Berlin. Olga is interested in theoretical foundations and practical algorithms for digital content creation tasks, such as shape representation and editing, artistic modeling techniques, computer animation and digital image manipulation. She also works on fundamental problems in digital geometry processing, including reconstruction, parameterization, filtering and compression of geometric data. Olga received the EUROGRAPHICS Young Researcher Award (2008), the ACM SIGGRAPH Significant New Researcher Award (2011), the ERC Starting Grant (2012), the ETH Latsis Prize (2012) and the Intel Early Career Faculty Award (2013).

Homepage: http://igl.ethz.ch/people/sorkine


Daniel CremersTitle: Novel Algorithms for Non-Rigid 3D Shape Analysis

Abstract:
With novel algorithms for 3D reconstruction from standard cameras,
range scanners or RGB-D cameras an increasing number of digitized
three-dimensional objects is becoming available.  In my presentation,
I will introduce novel algorithms to analyze three-dimensional shapes.
In the first part, I will introduce a novel algorithm to compute a
dense elastic matching of shapes.  More specifically, we propose to
minimize an elastic thin-shell energy between two given 3D shapes by
means of large-scale linear programming relaxations.  In the second
part, I will introduce the Wave Kernel Signature as a novel feature
descriptor for shape analysis.  It is defined as the time-averaged
probability to detect quantum mechanical particles at respective
points of the shape.  In numerous experiments, I will show that it is
well suited for various challenges of shape analysis ranging from
correspondence finding and matching to shape decomposition.


Bio:
Daniel Cremers is a professor for Computer Science and Mathematics at the Technical University of Munich. He received Bachelor degrees in
Mathematics (1994) and Physics (1994), and a Master's degree in Theoretical Physics (1997) from the University of Heidelberg. In 2002
he obtained a PhD in Computer Science from the University of Mannheim, Germany.  Subsequently he spent two years as a postdoc at the
University of California at Los Angeles and one year as a permanent researcher at Siemens Corporate Research (Princeton). From 2005 until
2009 he was associate professor at the University of Bonn, Germany. Since 2009 he holds the chair for Computer Vision and Pattern
Recognition at the Technical University of Munich. Daniel is interested in computer vision and optimization with a particular focus
on image-based 3D reconstruction, 3D shape analysis and convex variational methods. His publications received several awards,
including the Best Paper of the Year 2003 by the Int. Pattern Recognition Society, the Olympus Award 2004 by the German Pattern
Recognition Society and the 2005 UCLA Chancellor's Award for Postdoctoral Research. He is recipient of an ERC Starting Grant (2009)
and an ERC Proof of Concept Grant (2014).  In December 2010 the magazine Capital listed Prof. Cremers among "Germany's Top 40
Researchers Below 40".
Homepage: http://vision.in.tum.de/members/cremers