Recent Trends, Applications, and Perspectives in 3D Shape Similarity Assessment
No Thumbnail Available
Date
2016
Journal Title
Journal ISSN
Volume Title
Publisher
Copyright © 2016 The Eurographics Association and John Wiley & Sons Ltd.
Abstract
The recent introduction of 3D shape analysis frameworks able to quantify the deformation of a shape into another in terms of the variation of real functions yields a new interpretation of the 3D shape similarity assessment and opens new perspectives. Indeed, while the classical approaches to similarity mainly quantify it as a numerical score, map‐based methods also define (dense) shape correspondences. After presenting in detail the theoretical foundations underlying these approaches, we classify them by looking at their most salient features, including the kind of structure and invariance properties they capture, as well as the distances and the output modalities according to which the similarity between shapes is assessed and returned. We also review the usage of these methods in a number of 3D shape application domains, ranging from matching and retrieval to annotation and segmentation. Finally, the most promising directions for future research developments are discussed.The recent introduction of 3D shape analysis frameworks able to quantify the deformation of a shape into another in terms of the variation of real functions yields a new interpretation of the 3D shape similarity assessment and opens new perspectives. Indeed, while the classical approaches to similarity mainly quantify it as a numerical score, map‐based methods also define (dense) shape correspondences.
Description
@article{10.1111:cgf.12734,
journal = {Computer Graphics Forum},
title = {{Recent Trends, Applications, and Perspectives in 3D Shape Similarity Assessment}},
author = {Biasotti, S. and Cerri, A. and Bronstein, A. and Bronstein, M.},
year = {2016},
publisher = {Copyright © 2016 The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/cgf.12734}
}