EG2014 - STARs

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https://diglib.eg.org/handle/10.2312/7707

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Browsing EG2014 - STARs by Subject "Computational Geometry and Object Modeling"

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    Physically-based Simulation of Cuts in Deformable Bodies: A Survey
    (The Eurographics Association, 2014) Wu, Jun; Westermann, Rüdiger; Dick, Christian; Sylvain Lefebvre and Michela Spagnuolo
    Virtual cutting of deformable bodies has been an important and active research topic in physically-based simulation for more than a decade. A particular challenge in virtual cutting is the robust and efficient incorporation of cuts into an accurate computational model that is used for the simulation of the deformable body. This report presents a coherent summary of the state-of-the-art in virtual cutting of deformable bodies, focusing on the distinct geometrical and topological representations of the deformable body, as well as the specific numerical discretizations of the governing equations of motion. In particular, we discuss virtual cutting based on tetrahedral, hexahedral, and polyhedral meshes, in combination with standard, polyhedral, composite, and extended finite element discretizations. A separate section is devoted to meshfree methods. The report is complemented with an application study to assess the performance of virtual cutting simulators.
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    Quantifying 3D Shape Similarity Using Maps: Recent Trends, Applications and Perspectives
    (The Eurographics Association, 2014) Biasotti, S.; Cerri, A.; Bronstein, A.; Bronstein, M.; Sylvain Lefebvre and Michela Spagnuolo
    Shape similarity is an acute issue in Computer Vision and Computer Graphics that involves many aspects of human perception of the real world, including judged and perceived similarity concepts, deterministic and probabilistic decisions and their formalization. 3D models carry multiple information with them (e.g., geometry, topology, texture, time evolution, appearance), which can be thought as the filter that drives the recognition process. Assessing and quantifying the similarity between 3D shapes is necessary to explore large dataset of shapes, and tune the analysis framework to the user's needs. Many efforts have been done in this sense, including several attempts to formalize suitable notions of similarity and distance among 3D objects and their shapes. In the last years, 3D shape analysis knew a rapidly growing interest in a number of challenging issues, ranging from deformable shape similarity to partial matching and view-point selection. In this panorama, we focus on methods which quantify shape similarity (between two objects and sets of models) and compare these shapes in terms of their properties (i.e., global and local, geometric, differential and topological) conveyed by (sets of) maps. After presenting in detail the theoretical foundations underlying these methods, we review their usage in a number of 3D shape application domains, ranging from matching and retrieval to annotation and segmentation. Particular emphasis will be given to analyse the suitability of the different methods for specific classes of shapes (e.g. rigid or isometric shapes), as well as the flexibility of the various methods at the different stages of the shape comparison process. Finally, the most promising directions for future research developments are discussed.