Symmetry descriptors and 3D shape matching

By M. Kazhdan, Thomas A. Funkhouser, Szymon Rusinkiewicz. 2004

209 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computer Vision and Pattern Recognition

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In Computational Mechanics

In Computer Vision and Pattern Recognition

Citations in the corpus

Learning to Reconstruct Shapes from Unseen Classes (2018, methodology): “Spherical projections have been shown effective in 3D shape retrieval [Esteves et al., 2018], classification [Cao et al., 2017], and finding possible rotational as well as reflective symmetries [Kazhdan et al., 2004, 2002].”
Shape google: Geometric words and expressions for invariant shape retrieval (2011, methodology): “…global descriptors based on volume and area [Zhang and Chen 2001], wavelets [Paquet et al. 2000], statistical moments [Kazhdan et al. 2003; Novotni and Klein 2003; Tal et al. 2001], self-similarity (symmetry) [Kazhdan et al. 2004], and distance distributions [Osada et al. 2002] were used.”
Curve skeleton extraction from incomplete point cloud (2009, background): “There has been a great deal of recent research on symmetry detection and symmetry-aware geometry processing, e.g., [Kazhdan et al. 2004; Mitra et al. 2006; Podolak et al. 2006; Ovsjanikov et al. 2008], to name a few.”
Deformation-driven shape correspondence via shape recognition (2017, background): “Man-made objects typically exhibit major global symmetries aligning with their perceptually principal directions [Kazhdan et al. 2004; Podolak et al. 2006].”
A planar-reflective symmetry transform for 3D shapes (2006, methodology): “Instead, we use the Gaussian Euclidean Distance Transform (GEDT), as was previously proposed by [Kazhdan et al. 2004].”
Approximate Symmetry Detection in Partial 3D Meshes (2014, methodology): “In this direction, Kazhdan et al. [KFR04] formulated an efﬁcient procedure to evaluate the symmetry measure us-ing spherical harmonic coefﬁcients.”
Robust global registration (2005, unknown): “We expect that this method can be extended to be able to detect partial symmetries in the shape, which is not possible using existing methods for symmetry detection [KFR04].”
Shape from symmetry (2005, background): “As argued in [8], many man-made and natural objects are symmetric, or possess parts that are symmetric [14].”
Partial and approximate symmetry detection for 3D geometry (2006, methodology): “Later they extended this work to rotational symmetries and used it for shape retrieval for database matching in [Kazhdan et al. 2004].”