Geometric and Topological Methods for Imaging, Graphics and Networks

Dear Colleagues,

While computer science is generally not associated with geometry (and even less with topology), and practitioners in the field are, as a norm, far from being geometrically inclined, the fields of imaging and graphics stand apart. Indeed, not only are geometrical and topological methods widely used, and even prevalent, in these intensively active areas of study, they represent the main core of paradigms and tools employed. In fact, one might say—only slightly exaggerating—that large tracts of imaging and practically all of the research in graphics represents nothing else but the direct application and concrete “crystallization” of many important ideas and techniques in geometry and topology.

Mindful of this essential fact, we invite our colleagues labouring in the disciplines of imaging and graphics to submit papers illustrating the multifaceted roles of geometry and topology in the present state-of-the-art research. In particular, papers are welcomed appertaining to all areas of geometry, being it differential, projective or algebraic, smooth, discrete, or digital, as well as their manifold applications to segmentation, feature extraction, texture modelling, classification, face recognition, manifold learning, and many others. In particular, articles emphasizing the role and usefulness of the notion of curvature in all its manifold incarnations are invited. Contributions involving topological tools and applications for graphics and imaging applications, involving the study of surfaces and of higher-dimensional manifolds and more generalized structures are also appreciated.

Prof. Dr. Emil Saucan
Prof. Dr. David Gu
Guest Editors

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