VisLunch/Spring2010 - Revision history

Jlevine at 15:23, 18 June 2010

2010-06-18T15:23:32Z

← Older revision		Revision as of 15:23, 18 June 2010
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	data-driven shape morphing.		data-driven shape morphing.

	- ''Speaker:'' Olga Symonova (GA Tech), http://ecotheory.biology.gatech.edu/olga/main.htm		- ''Speaker:'' Olga Symonova (Georgia Tech), http://ecotheory.biology.gatech.edu/olga/main.htm

	- ''Where:'' Conference Room 3760		- ''Where:'' Conference Room 3760

Jlevine: /* June 25, 2010 */

2010-06-18T15:16:27Z

June 25, 2010

← Older revision		Revision as of 15:16, 18 June 2010
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	== June 18, 2010 ==		== June 25, 2010 ==

	- '''Shape Analysis and Understanding'''		- '''Shape Analysis and Understanding'''
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	- ''Where:'' Conference Room 3760		- ''Where:'' Conference Room 3760

	- ''When:'' Friday noon (06/18)		- ''When:'' Friday noon (06/25)

	== June 11, 2010 ==		== June 11, 2010 ==

Jlevine at 15:15, 18 June 2010

2010-06-18T15:15:37Z

← Older revision		Revision as of 15:15, 18 June 2010
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	cancel any future weeks.		cancel any future weeks.
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			== June 18, 2010 ==

			- '''Shape Analysis and Understanding'''

			In the first part of the talk, I will present my doctoral research on
			3D shape description for retrieval purposes. I will describe the use
			of a Reeb-graph based shape descriptor and the Fiedler vector of its
			Laplacian matrix for shape matching.

			In the second part of the talk I will present an ongoing research
			project which aims at understanding the genetic basis of root traits
			of crop plants. This project with applications in biology is analogous
			to an open research problem on how to bridge the shape of an object
			with its semantics. Known genome sequences of some crops, like rice or
			corn, represent the functional meaning of the shape, aka its
			semantics. From the other side, a description of the shape of roots is
			lacking due to the natural non-transparent growth media which makes it
			difficult to acquire and analyze the shape of roots. The results of
			the early acquisition process produce noisy data with complex spatial
			structure. Within this framework, we are interested in the analysis of
			time-series 3D data, and, more precisely, in the computation of
			global, local, and dynamic shape descriptors of roots. As a first step
			in this direction, we extract a curve skeleton representing root
			structure which is robust to noise. Using this skeleton we are able to
			compute various local and global shape descriptors, and move towards
			analysis of time-series data.

			In the conclusion of the talk, I will discuss some applications of
			shape analysis and description which are inspiring me for future work,
			such as: robust methods for extraction of complex data in medical and
			biological applications; definition of meaningful shape features;
			analysis and similarity estimation of large physical networks; and
			data-driven shape morphing.

			- ''Speaker:'' Olga Symonova (GA Tech), http://ecotheory.biology.gatech.edu/olga/main.htm

			- ''Where:'' Conference Room 3760

			- ''When:'' Friday noon (06/18)

	== June 11, 2010 ==		== June 11, 2010 ==

Jlevine: /* June 11, 2010 */

2010-06-08T16:22:16Z

June 11, 2010

← Older revision		Revision as of 16:22, 8 June 2010
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	The emergence of freeform structures in contemporary architecture raises numerous challenging research problems, most of which are related to the actual fabrication and are a rich source of research topics in geometry and geometric computing. The talk will provide an overview of recent progress in this field, with a particular focus on projects which illustrate the transfer of research into the architectural practice.		The emergence of freeform structures in contemporary architecture raises numerous challenging research problems, most of which are related to the actual fabrication and are a rich source of research topics in geometry and geometric computing. The talk will provide an overview of recent progress in this field, with a particular focus on projects which illustrate the transfer of research into the architectural practice.

	- ''Speaker:'' Helmut Pottmann (KAUST), Director of the Geometric Modeling and Scientific Visualization Research Center and Professor of Applied Mathematics and Computational Science in the Mathematical and Computer Sciences and Engineering Division http://www.kaust.edu.sa/academics/faculty/pottmann.html		- ''Speaker:'' Helmut Pottmann (KAUST), Director of the Geometric Modeling and Scientific Visualization Research Center and Professor of Applied Mathematics and Computational Science in the Mathematical and Computer Sciences and Engineering Division

			http://www.kaust.edu.sa/academics/faculty/pottmann.html

	- ''Where:'' Conference Room 3760		- ''Where:'' Conference Room 3760

Jlevine at 16:21, 8 June 2010

2010-06-08T16:21:38Z

← Older revision		Revision as of 16:21, 8 June 2010
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	cancel any future weeks.		cancel any future weeks.
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			== June 11, 2010 ==

			- '''Advances in Architectural Geometry – Research and Practice'''

			The emergence of freeform structures in contemporary architecture raises numerous challenging research problems, most of which are related to the actual fabrication and are a rich source of research topics in geometry and geometric computing. The talk will provide an overview of recent progress in this field, with a particular focus on projects which illustrate the transfer of research into the architectural practice.

			- ''Speaker:'' Helmut Pottmann (KAUST), Director of the Geometric Modeling and Scientific Visualization Research Center and Professor of Applied Mathematics and Computational Science in the Mathematical and Computer Sciences and Engineering Division http://www.kaust.edu.sa/academics/faculty/pottmann.html

			- ''Where:'' Conference Room 3760

			- ''When:'' Friday noon (06/11)

	== June 4, 2010 ==		== June 4, 2010 ==

Jlevine: /* June 4, 2010 */

2010-06-02T06:41:13Z

June 4, 2010

← Older revision		Revision as of 06:41, 2 June 2010
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	underlying manifold. A clear limitation of this problem is that the object		underlying manifold. A clear limitation of this problem is that the object
	may not be a manifold but a stratified space, the space which can be		may not be a manifold but a stratified space, the space which can be
	partitioned into strata, each of which are manifolds. In this ~~abstract~~, we		partitioned into strata, each of which are manifolds. In this work, we
	study the following problem: given a point cloud sampled from a stratified		study the following problem: given a point cloud sampled from a stratified
	space, which points belong to the same strata? This inference problem is		space, which points belong to the same strata? This inference problem is
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	- ''When:'' Friday noon (06/04)		- ''When:'' Friday noon (06/04)


	== May 21, 2010 ==		== May 21, 2010 ==

Jlevine at 04:41, 2 June 2010

2010-06-02T04:41:58Z

← Older revision		Revision as of 04:41, 2 June 2010
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	geometric inference statement, and a probabilistic inference statement. The		geometric inference statement, and a probabilistic inference statement. The
	approach we describe holds for Whitney stratified spaces.		approach we describe holds for Whitney stratified spaces.


	- ''Speaker:'' Bei Wang (Duke), http://www.cs.duke.edu/~beiwang/		- ''Speaker:'' Bei Wang (Duke), http://www.cs.duke.edu/~beiwang/
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	Direct volume rendering techniques have been successfully applied to visualizing volumetric datasets across many application domains. Due to the sensitivity of transfer functions and the complexity of fine-tuning transfer functions, direct volume rendering is still not widely used in practice. For fast volumetric data exploration, we propose Importance-Based Accumulated Transparency Modulation which does not rely on transfer function manipulation. This novel rendering algorithm is a generalization and extension of the Maximum Intensity Difference Accumulation technique. By only modifying the accumulated transparency, the resulted volume renderings are essentially high dynamic range. We show that by using several common importance measures, different features of the volumetric datasets can be highlighted. The results can be easily extended to a high-dimensional importance difference space, by mixing the results from an arbitrary number of importance measures with weighting factors, which all control the final output with a monotonic behavior. With Importance-Based Accumulated Transparency Modulation, the end-user can explore a wide variety of volumetric datasets quickly without the burden of manually setting and adjusting a transfer function.		Direct volume rendering techniques have been successfully applied to visualizing volumetric datasets across many application domains. Due to the sensitivity of transfer functions and the complexity of fine-tuning transfer functions, direct volume rendering is still not widely used in practice. For fast volumetric data exploration, we propose Importance-Based Accumulated Transparency Modulation which does not rely on transfer function manipulation. This novel rendering algorithm is a generalization and extension of the Maximum Intensity Difference Accumulation technique. By only modifying the accumulated transparency, the resulted volume renderings are essentially high dynamic range. We show that by using several common importance measures, different features of the volumetric datasets can be highlighted. The results can be easily extended to a high-dimensional importance difference space, by mixing the results from an arbitrary number of importance measures with weighting factors, which all control the final output with a monotonic behavior. With Importance-Based Accumulated Transparency Modulation, the end-user can explore a wide variety of volumetric datasets quickly without the burden of manually setting and adjusting a transfer function.


	- ''Speaker:'' Yong Wan (SCI), http://www.sci.utah.edu/people/wanyong.html		- ''Speaker:'' Yong Wan (SCI), http://www.sci.utah.edu/people/wanyong.html

Jlevine at 04:41, 2 June 2010

2010-06-02T04:41:39Z

← Older revision		Revision as of 04:41, 2 June 2010
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	cancel any future weeks.		cancel any future weeks.
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			== June 4, 2010 ==

			- '''Stratification Learning Through Homology Inference'''

			A basic problem in geometry, topology, and statistical inference that has
			received recent attention is that of manifold learning: given a point cloud
			of data sampled from a manifold in an ambient space R^k, infer the
			underlying manifold. A clear limitation of this problem is that the object
			may not be a manifold but a stratified space, the space which can be
			partitioned into strata, each of which are manifolds. In this abstract, we
			study the following problem: given a point cloud sampled from a stratified
			space, which points belong to the same strata? This inference problem is
			examined from three perspectives, a topological inference statement, a
			geometric inference statement, and a probabilistic inference statement. The
			approach we describe holds for Whitney stratified spaces.


			- ''Speaker:'' Bei Wang (Duke), http://www.cs.duke.edu/~beiwang/

			- ''Where:'' Conference Room 3760

			- ''When:'' Friday noon (06/04)


	== May 21, 2010 ==		== May 21, 2010 ==

Jlevine: /* May 21, 2010 */

2010-05-07T06:50:17Z

May 21, 2010

← Older revision		Revision as of 06:50, 7 May 2010
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	- ''Speaker:'' Yong Wan (SCI~~, graduate student~~), http://www.sci.utah.edu/people/wanyong.html		- ''Speaker:'' Yong Wan (SCI), http://www.sci.utah.edu/people/wanyong.html

	- ''Where:'' Conference Room 3760		- ''Where:'' Conference Room 3760

	- ''When:'' Friday noon (05/21)		- ''When:'' Friday noon (05/21)


	== May 14, 2010 ==		== May 14, 2010 ==

Jlevine: /* May 7, 2010 */

2010-05-07T06:50:07Z

May 7, 2010

← Older revision		Revision as of 06:50, 7 May 2010
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	non-manifolds.		non-manifolds.

	- ''Speaker:'' Kuiyu Li (~~OSU, graduate student~~), http://www.cse.ohio-state.edu/~liku/		- ''Speaker:'' Kuiyu Li (Ohio State University), http://www.cse.ohio-state.edu/~liku/

	- ''Where:'' Conference Room 3760		- ''Where:'' Conference Room 3760

	- ''When:'' Friday noon (05/07)		- ''When:'' Friday noon (05/07)


	== Apr. 16, 2010 ==		== Apr. 16, 2010 ==