Invited speakers

Eric Andres

University of Poitiers, France

Title: Digital Swept Tubes

Abstract: In this presentation we are going to show how it is possible to construct digital tubes in a very simple and straight-forward way based on a 3D parametric curve and a profile that can be based on an implicite 2D curve or a shape extracted from a binary image. One of the main characteristic of this generation method is that the digital tubes have a controlled topology in the sense that we control its k-separability. Extensions to digital tubular tree structures are also possible.
As an appetizer you can look up some of the examples on the following site.

Helmut Pottmann

TU Wien, Austria

Title: Freeform Architecture and Discrete Differential Geometry

Abstract: Free forms constitute one of the major trends within contemporary architecture. While the digital design of freeform geometry with current modeling tools is well understood, the actual fabrication on the architectural scale is a big challenge: one has to decompose the skins into manufacturable panels, provide appropriate support structures, meet structural constraints and last, but not least make sure that the cost does not become excessive. These practical requirements form a rich source of research topics in geometry and geometric computing. The speaker will report on recent progress in geometric computing for freeform architecture, with special emphasis on the close relation to discrete differential geometry. Specific topics to be addressed include: meshes with planar quadrilateral faces and corresponding supporting structures, polyhedral patterns, semi-discrete representations for structures from single curved panels, and the design of structures in force equilibrium. The transfer of research into the architectural practice will be illustrated at hand of selected projects.

Michael Wilkinson

University of Groningen, Nederland

Title: A Guided Tour of Connective Morphology: Concepts, Algorithms, and Applications

Abstract: Connective morphology has been an active area of research for more than two decades. Based on an abstract notion of connectivity, it allows development of perceptual grouping of pixels using different connectivity classes. Images are processed based on these perceptual groups, rather than some rigid neighbourhood imposed upon the image in the form of a fixed structuring element. The progress in this field has been threefold: (i) development of a mathematical framework; (ii) development of fast algorithms, and (iii) application of the methodology in very diverse fields. In this talk I will review these developments, and describe relationships to other image-adaptive methods. I will also discuss the opportunities for use in multi-scale analysis and inclusion of machine learning within connected filters.