IEEE Transactions on Pattern Analysis and Machine Intelligence
Volumetric shapes of solids of revolution from a single-view range image
CVGIP: Image Understanding
A Hough transform technique for the detection of rotational symmetry
Pattern Recognition Letters
Assembling virtual pots from 3D measurements of their fragments
Proceedings of the 2001 conference on Virtual reality, archeology, and cultural heritage
Bayesian Pot-Assembly from Fragments as Problems in Perceptual-Grouping and Geometric-Learning
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Estimating a-priori Unknown 3D Axially Symmetric Surfaces from Noisy Measurements of Their Fragments
3DPVT '06 Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06)
Digital Imaging for Cultural Heritage Preservation: Analysis, Restoration, and Reconstruction of Ancient Artworks
Determination of ancient manufacturing techniques of ceramics by 3d shape estimation
VSMM'06 Proceedings of the 12th international conference on Interactive Technologies and Sociotechnical Systems
Fast axis estimation from a segment of rotationally symmetric object
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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This paper proposes a new method for estimating the symmetric axis of a pottery from its small fragment using surface geometry. Also, it provides a scheme for grouping such fragments into shape categories using distribution of surface curvature. For automatic assembly of pot from broken sherds, axis estimation is an important task and when a fragment is small, it is difficult to estimate axis orientation since it looks like a patch of a sphere and conventional methods mostly fail. But the proposed method provides fast and robust axis estimation by using multiple constraints. The computational cost is also too lowered. To estimate the symmetric axis, the proposed algorithm uses three constraints: (1) The curvature is constant on a circumference C"H. (2) The curvature is invariant in any scale. (3) Also the principal curvatures does not vary on C"H. C"H is a planar circle which is one of all the possible circumferences of a pottery or sherd. A hypothesis test for axis is performed using maximum likelihood. The variance of curvature, multi-scale curvature and principal curvatures is computed in the likelihood function. We also show that the principal curvatures can be used for grouping of sherds. The grouping of sherds will reduce the computation significantly by omitting impossible configurations in broken pottery assembly process.