Detecting mirror-symmetry of a volumetric shape from its single 2D image

Sawada, Tadamasa; Pizlo, Zygmunt

doi:10.1109/cvprw.2008.4562976

Cited by 3 publications

(2 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Chaouch and Verroust-Blondet [2] introduced four types of reflection symmetries, which are cyclic (several mirror planes passing through a fixed axis), dihedral (several mirror planes passing through a fixed axis with one perpendicular to the axis), rotational symmetry (looks similar after rotation, e.g., different platonic solids, like tetrahedron, octahedron, icosahedron and dodecahedron) and unique symmetry (only one mirror plane, for instance, many natural and most man-made objects). Most symmetric objects are mirror rather than rotational symmetric [10].…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Efficient 3D reflection symmetry detection: A view-based approach

Johan²,

et al. 2016

Graphical Models

View full text Add to dashboard Cite

Section: Related Workmentioning

confidence: 99%

“…Sawada and Pizlo [10,17] performed symmetry detection based on a single 2D image of a volumetric shape. First, a polyhedron is recovered from the single 2D image based on a set of constraints including 3D shape symmetry, minimum surface area, maximum 3D compactness and maximum planarity of contours.…”

Section: Related Workmentioning

confidence: 99%

Efficient 3D reflection symmetry detection: A view-based approach

Johan²,

et al. 2016

Graphical Models

View full text Add to dashboard Cite

Visual detection of symmetry of 3D shapes

Sawada¹

2010

Journal of Vision

View full text Add to dashboard Cite

This study tested perception of symmetry of 3D shapes from single 2D images. In Experiment 1, performance in discrimination between symmetric and asymmetric 3D shapes from single 2D line drawings was tested. In Experiment 2, performance in discrimination between different degrees of asymmetry of 3D shapes from single 2D line drawings was tested. The results showed that human performance in the discrimination was reliable. Based on these results, a computational model that performs the discrimination from single 2D images is presented. The model first recovers the 3D shape using a priori constraints: 3D symmetry, maximal 3D compactness, minimum surface area, and maximal planarity of contours. Then the model evaluates the degree of symmetry of the 3D shape. The model provided good fit to the subjects' data.

show abstract