Elsevier CAGD – Computer-Aided Geometric Design

Special Issue on “Heat Diffusion Equation and Optimal Transport in Geometry Processing and Computer Graphics”

Guest Editors: David Xianfeng Gu (Stony Brook University, USA), Giuseppe Patanè (CNR-IMATI, Italy)

Theme. In geometry processing and shape analysis, several problems and applications have been addressed through the properties of the solution to the heat diffusion equation and to the optimal transport. For instance, diffusion kernels allow us to define diffusion distances, shape descriptors and clustering methods, to approximate geodesics and optimal transport distances, to deform 3D shapes, to smooth and approximate signals in a multi-scale fashion. Optimal transport has been successfully applied to volume parameterization, surface registration, inter-surface mapping, shape matching and comparison. Furthermore, the heat diffusion equation and the optimal transport are intrinsically correlated and central in different research fields, such as Computer Graphics, Geometry, Manifold Learning, and Differential Equations.

Main topics. This Special Section of the CAGD Journal, published by Elsevier, covers a range of topics on the properties, discretization, computation, and applications of the heat equation and the optimal transport in the context of Computer Graphics, Computer-Aided Geometric Design, and related research fields. The topics range from geometry processing to high-level understanding of 3D shapes, and more generally n-dimensional data, including feature extraction, segmentation, and matching. The list of suggested topics includes but is not limited to:
· Heat diffusion equation
· Diffusion kernels and distances
· Diffusion shape descriptors
· Multi-scale modeling and approximation
· Optimal transport
· Wasserstein distance
· Geometry processing applications
· Surface parameterization
· Shape modelling applications
· Shape matching and comparison
· Dynamic surface tracking
· Shape analysis and retrieval
· Shape correspondence and registration
· Manifold learning
· Generative model in Machine Learning
· Clustering and dimensionality reduction
· Applications to Geometry Processing
· Applications to Computer Graphics
· Applications to Computational Geometry
· Applications to 3D Printing
· Applications to Material Design
· Applications to Computer Vision
· Applications to Medicine (e.g., brain and neuro-imaging)

Manuscript preparation and submission This thematic issue seeks high-quality research, survey, theory and application submissions. Papers must be original contributions, not previously published or currently under-review in other journals. Submissions based on previous published or submitted conference papers may be considered provided they are considerably improved and extended.

Instructions for authors available at https://www.elsevier.com/journals/computer-aided-geometric-design/0167-8396/guide-for-authors

Journal and Submission URL https://www.journals.elsevier.com/computer-aided-geometric-design (selecting the option SI:HEAT&TRANSPORT)

For information, please contact Giuseppe Patanè patane@ge.imati.cnr.it

Timeline
· Full paper submission: 19 February 2018
· Notification of the 1st review process: 28 March 2018
· Revised version due: 30 April 2018
· Notification of acceptance: 15 May 2018
· Camera ready copy due: 31 May 2018