Topological, Geometric and Structural Approaches to Enhance Shape Information

Abstract

Nowadays, the increasing power of hardware components has made available a huge amount of digital models, more and more complex and detailed, as needed in many innovative research fields such as medical imaging, entertainment, product modelling and design. In this scenario, both industry and academy feel an urgent need of tools to efficiently describe, recognise and retrieve shapes, which usually require to enhance the raw geometry with additional high-level shape information. Analyzing and enhancing geometry is the basis for an efficient understanding of shapes, and has been for many years one of the most challenging issues at IMATI-GE/CNR. Recent advances in the field of semantic-based knowledge systems dealing with multi-dimensional media boosted this research field significantly, and the Shape Modeling Group at IMATI-GE/CNR produced several innovative methods that are reviewed in this paper. Approaches are classified and described along with some results, and discussed with respect to applications. Open issues are outlined along with future research plans.