Invariant surface characteristics for 3D object recognition in range images
Computer Vision, Graphics, and Image Processing - Lectures notes in computer science, Vol. 201 (G. Goos and J. Hartmanis, Eds.)
SIAM Journal on Computing
Smoothing and matching of 3-D space curves
International Journal of Computer Vision
Active shape models—their training and application
Computer Vision and Image Understanding
Normal vector voting: crease detection and curvature estimation on large, noisy meshes
Graphical Models - Special issue: Processing on large polygonal meshes
Intrinsic Surface Properties from Surface Triangulation
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Rigid and Affine Registration of Smooth Surfaces using Differential Properties
ECCV '94 Proceedings of the Third European Conference-Volume II on Computer Vision - Volume II
Best Fit Surface Curvature at Vertices of Topologically Irregular Curve Networks
Proceedings of the 6th IMA Conference on the Mathematics of Surfaces
Estimating the tensor of curvature of a surface from a polyhedral approximation
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
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The detection and modeling of the human spine from scanned 3D data is an important issue in biomedical shape analysis. It can be useful for avoiding invasive treatments like radiographs, taken for the purpose of monitoring spine deformations and its correction, as is the cases in scoliosis. This is especially important with children. This work presents a new method for the detection of the human spine from 3D models of human backs formed by triangular meshes, and taken with a range sensor. The method is based on the estimation of the principal curvatures directions, and by joining valley points along these directions. Results are presented with the method applied to scanned 3D models of real patients.