A planar-reflective symmetry transform for 3D shapes

By Joshua Podolak, Philip Shilane, Aleksey Golovinskiy, Szymon Rusinkiewicz, Thomas A. Funkhouser. ACM Transactions on Graphics, 2006

385 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/4067a5de7f9670481986546914ba14fefdb4b5ab

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Mechanics

In Computer Vision and Pattern Recognition

Citations in the corpus

Segmentation and Unsupervised Part-based Discovery of Repetitive Objects (2010, background): “In 3D, discovery and utilization of repetition has been adressed in computer aided design and other synthetic models [7, 8, 9].”
A Symmetry Prior for Convex Variational 3D Reconstruction (2016, methodology): “Symmetries have also been used for many applications, e.g. shape matching and feature point matching [6], object part segmentation, and canonical coordinate frame selection [23].”
Data-driven suggestions for creativity support in 3D modeling (2010, background): “Global reflective symmetry is respected during segmentation [Podolak et al. 2006].”
Probabilistic reasoning for assembly-based 3D modeling (2011, background): “Our implementation supports planar reflective symmetry, which is among the most prevalent in real-world objects [Podolak et al. 2006].”
The Columbia grasp database (2009, methodology): “Better alignment might be obtained using a different global transform, such as the Principal Symmetry Axes transform [17] or by using a pairwise alignment method such as Iterative Closest Point.”
PCN: Point Completion Network (2018, methodology): “Symmetry-driven methods [28, 29, 34, 35, 45, 51, 54] identify symmetry axes and repeating regular structures in the partial input in order to copy parts from observed regions to unobserved regions.”
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.”
Data-driven structural priors for shape completion (2015, methodology): “[2012] Podolak et al.[2006]”
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].”
Discovering Structural Regularity in 3D Geometry (2008, methodology): “Following the sampling approach proposed in [Podolak et al. 2006] and [Mitra et al. 2006], we first compute a uniform random sampling of the input model S with average sample spacing h.”
Learning to group discrete graphical patterns (2017, neutral): “Many techniques have been developed for exact and approximate symmetry detection of patterns found in natural images and shapes, e.g., [Barnes et al. 2010; Graham et al. 2010; Lukac et al. 2017; Podolak et al. 2006]; see also surveys by [Liu et al. 2010; Mitra et al. 2012].”