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A Salience Measure for 3D Shape Decomposition and Sub-parts Classification

Thibault Blanc-Beyne 1, 2 Géraldine Morin 1 Kathryn Leonard 3 Stefanie Hahmann 4 Axel Carlier 1, 2
1 IRIT-REVA - Real Expression Artificial Life
IRIT - Institut de recherche en informatique de Toulouse
4 IMAGINE [2016-2019] - Intuitive Modeling and Animation for Interactive Graphics & Narrative Environments [2016-2019]
Inria Grenoble - Rhône-Alpes, Grenoble INP [2007-2019] - Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019], LJK - Laboratoire Jean Kuntzmann
Abstract : This paper introduces a measure of significance on a curve skeleton of a 3D piecewise linear shape mesh, allowing the computation of both the shape's parts and their saliency. We begin by reformulating three existing pruning measures into a non-linear PCA along the skeleton. From this PCA, we then derive a volume-based salience measure, the 3D WEDF, that determines the relative importance to the global shape of the shape part associated to a point of the skeleton. First, we provide robust algorithms for computing the 3D WEDF on a curve skeleton, independent on the number of skeleton branches. Then, we cluster the WEDF values to partition the curve skeleton, and coherently map the decomposition to the associated surface mesh. Thus, we develop an unsupervised hierarchical decomposition of the mesh faces into visually meaningful shape regions that are ordered according to their degree of perceptual salience. The shape analysis tools introduced in this paper are important for many applications including shape comparison, editing, and compression.
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Submitted on : Monday, July 16, 2018 - 12:04:35 PM
Last modification on : Tuesday, October 6, 2020 - 12:44:47 PM
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Thibault Blanc-Beyne, Géraldine Morin, Kathryn Leonard, Stefanie Hahmann, Axel Carlier. A Salience Measure for 3D Shape Decomposition and Sub-parts Classification. Graphical Models, Elsevier, 2018, 99, pp.22-30. ⟨10.1016/j.gmod.2018.07.003⟩. ⟨hal-01840016⟩



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