Christoph Schnörr

Institute of Applied Mathematics, University of Heidelberg

Image Segmentation and Understanding: A Challenge for Mathematicians IP3

The tremendous need for the analysis of massive image data sets in many application areas has been mainly promoting pragmatic approaches to imaging analysis during the last years: adopt a computational model with adjustable parameters and predictive power. This development poses a challenge to the mathematical imaging community: (i) shift the focus from low-level problems (like denoising) to mid- and high-level problems of image analysis (a.k.a. image understanding); (ii) devise mathematical approaches and algorithms that advance our understanding of structure detection in image data beyond a set of rules for adjusting the parameters of black-box approaches. The purpose of this talk is to stimulate the corresponding discussion by sketching past and current major trends including own recent work.

Chair: Stacey Levine (Duquesne University)

The slides are available here.

  Wed 06 June at 08:15 Room A (Palazzina A - Building A, floor 0)