Research Activities

 

My research interests lie at the intersection of Engineering, for the aspects related to information systems, simulation engineering and modeling, signal processing, man-machine-interfaces, and Computer Science, for the aspects related to Computer Graphics, Computer Vision, and Multimedia. My overall research goal is the definition of a hierarchical paradigm for modeling and analyzing 3D shapes and multi-dimensional data, with applications to computer graphics, computer vision, geographic information systems, medicine, and bio-informatics. From 2001,  my research activities are focused mainly on numerical geometry and signal processing with piecewise linear and meshless approximations and on the geometric/topological analysis of 3D shapes for shape segmentation and semantic annotation.


Software Patent & Awards

  1. -Patent: Plumber: an interactive interface for multi-scale segmentation of triangulated surfaces. 30/09/2005, N. 003576, O. D004800, S.I.A.E., Italy.

  2. -GeoBigData 2015 Best Paper Award. G. Patanè, A. Cerri, V. Skytt, S. Pittaluga, S. Biasotti, D. Sobrero, T. Dokken, M. Spagnuolo. “A comparison of methods for the approximation and analysis of rainfall fields in environmental applications”. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol/issue II(3), Pages 523-530, 2015.

  3. -Computer & Graphics Excellence in Reviewing 2012.

  4. -Computer & Graphics Best Paper Award 2006. Mortara M., Patanè G., Spagnuolo M. “From geometric to semantic human body models”. In: Computers & Graphics, vol. 30 (2) pp. 185-196. Elsevier, 2006.

  5. -AIM@SHAPE Best Paper Award 2006. Saleem W., Schall O., Patanè G., Belyaev A., Seidel H. “On stochastic methods for surface reconstruction”. In: The Visual Computer, vol. 23 (6) pp. 381-395. Springer, 2007.

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  1. -Numerical geometry processing. This research activity has been focused on the unconstrained/constrained approximation of scalar functions and sparse implicit representations. More precisely, I have derived an approximation of the heat kernel that is scale covariant and robust to surface discretization, also addressing applications to shape analysis and comparison. Recent work has been focused on local barycentric coordinates [5] for shape deformation, on applications of implicit approximation to bioinformatics, and on semantic analysis [36, 37] for information visualization. Finally, the local and global parameterization of arbitrary 3D shapes have been addressed through a topology-driven chart decomposition.



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  1. -High-level and semantic analysis of shapes. These research activities have been focused on the iso- contouring of maps on point-sampled surfaces and on the computation of the Reeb graph on surfaces and point sets, with a minimal number of nodes and whose computational cost is lower than previous work. I have also proposed matching methods for 3D shapes, which are based on topological and point-based statistical shape descriptors, and machine learning. My research focused on feature lines’ extraction, on shape segmentation, and on the computation of structural descriptors built upon a multi-scale segmentation into shape features of 3D shapes represented as triangle meshes and point sets. For specific user scenarios, such as the analysis of virtual humans and object grasping, the structural description was turned into a semantic description and visualization.



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  1. -Modeling and analyzing multi-dimensional data. Starting from the variety of input data, my current research activities are mainly focused on processing multi-dimensional data and their attributes, without assumptions on their dimension, representation, and topology.