Working meeting "Visualization methods for uncertainty studies" - May, 22th 2017

Seminar organized between the GdR MASCOT-NUM and the GT Visualisation of the GdR IGRV

Organizers: Bertrand Iooss (EDF R&D, GdR MASCOT-NUM) and Julien Tierny (CNRS/LIP6, GT Visualisation/GdR IGRV)

It will take place on:

May 22, 2017, at Amphithéâtre Hermite, Institut Henri Poincaré, Paris.

Presentation of the workshop

L'objectif de ce séminaire est de se faire rencontrer des membres des communautés “visualisation” et “incertitudes”. Les exposés porteront sur des méthodes d'analyse d'incertitudes exploitant la visualisation, et des méthodes de visualisation (scientifique ou d'information) prenant en compte ou visant à analyser l'incertitude.



Agenda

Morning:

Afternoon:

Abstracts

Dimension reduction technique are used to visualize multidimensional data as scatterplots where points proximities match at best data dissimilarities. These techniques generate distortions of the data dissimilarities that may lead to erroneous inference of patterns in the data based on their visualization. I will present different techniques that display, correct or even take advantage of these uncertainties in multidimensional data analysis.

In this presentation, we will summarize some sources of uncertainty (in a broad sense, including imprecision) in images and related knowledge. We will then show how spatial imprecision can be modeled and represented using fuzzy sets. Models are of prime importance to guide the analysis and understanding of images. They can represent knowledge about acquisition geometry, noise statistics, object shape and appearance, etc. Structural models are also very useful to represent the spatial arrangement of structures, and the presentation will mostly focus on such models. Their use in spatial reasoning schemes allows for instance driving segmentation and recognition of structures in images. One important problem is related to the semantic gap. We will show that it can be addressed by generating spatial representations (in the image space) of relations expressed in linguistic or symbolic form, within a fuzzy sets formalism. This paradigm will be illustrated on various applications, in particular in medical imaging.

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