[Colloquium] Cancelled: Kai Li's MS Presentation

[Margaret Jaffey]

Kai Li’s MS Presentation has been cancelled and will be rescheduled for a later date.

Please watch for a new announcement early in spring quarter.


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Margaret Jaffey
margaret at cs.uchicago.edu
Department of Computer Science
Student Affairs Administrator
Ryerson 156
773-702-6011
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> On Mar 14, 2016, at 10:24 AM, Margaret Jaffey <margaret at cs.uchicago.edu> wrote:
> 
> This is a reminder about Kai Li's MS Presentation tomorrow.
> 
> ------------------------------------------------------------------------------
> Date:  Tuesday, March 15, 2016
> 
> Time:  10:00 AM
> 
> Place:  Ryerson 276
> 
> M.S. Candidate:  Kai Li
> 
> M.S. Paper Title: Connections Between Bandwidth Selection in Kernel
> Density Estimation and Mode Stability in Scale Space
> 
> Abstract:
> Technologies for scanned volumetric imaging (producing data on
> three-dimensional spatial or four-dimensional spatio-temporal grids)
> continue to grow in resolution and flexibility. As new imaging
> modalities are applied in new domains, the utility of
> application-specific and modality-specific tools decreases, and there
> is greater need for general purpose methods of finding and
> communicating structure in 3D/4D images. Scale-space is a conceptual
> framework that was studied and applied extensively for 2D projective
> images, but less so for 3D/4D data. We consider an image feature as a
> mathematically defined set of points in the image domain, such as
> critical points, edges, ridges, and valleys. We propose that the
> spatial stability of an image feature, respect to changes in scale
> (blurring, or diffusion), is an effective way to discern which
> features at a given scale are significant or ``real'', and to choose
> an optimum scale for that feature. This is conceptually rooted in the
> ``spatial coincidence assumption'' of Marr-Hildreth feature detection
> in classical computer vision, which selects edges that are spatially
> coincident over a range of scales as indicators of some significant
> underlying physical feature. Even when restricted to characterizing
> peaks (modes) in one-dimensional density distributions, there are
> interesting connections to other considerings of multi-scale feature
> selection, which we explore in this paper. Specifically, we identify
> the theoretical connection between our scale-space stability criterion
> and different approaches to bandwidth selection in kernel density
> estimation, such as the mean-shift vector method of D. Comaniciu et
> al. and the SiZer method of J. S. Marron et al.
> 
> Kai's advisor is Prof. Gordon Kindlmann
> 
> Login to the Computer Science Department website for details:
> https://www.cs.uchicago.edu/phd/ms_announcements#lik11
> 
> =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
> Margaret P. Jaffey            margaret at cs.uchicago.edu
> Department of Computer Science
> Student Support Rep (Ry 156)               (773) 702-6011
> The University of Chicago      http://www.cs.uchicago.edu
> =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
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