A syntactic/semantic technique for surface reconstruction from cross-sectional contours
Computer Vision, Graphics, and Image Processing
A framework for surface reconstruction from 3D contours
Computer Vision, Graphics, and Image Processing
Computer Processing of Line-Drawing Images
ACM Computing Surveys (CSUR)
Space Curve Representation and Recognition Based on Wavelet Transform Zero-Crossings
Journal of Mathematical Imaging and Vision
Invariant Representation and Matching of Space Curves
Journal of Intelligent and Robotic Systems
Nonparametric Segmentation of Curves into Various Representations
IEEE Transactions on Pattern Analysis and Machine Intelligence
3D trajectory matching by pose normalization
Proceedings of the 13th annual ACM international workshop on Geographic information systems
On Signature Invariants for Effective Motion Trajectory Recognition
International Journal of Robotics Research
Curvature and Torsion Estimators for 3D Curves
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
Topologically reliable approximation of composite Bézier curves
Computer Aided Geometric Design
Automated atlas-based clustering of white matter fiber tracts from DTMRI
MICCAI'05 Proceedings of the 8th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
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The Darboux vector contains both the curvature and torsion of a three-dimensional (3-D) image as its components. Curvature measures how sharply a curve is turning while torsion measures the extent of its twist in 3-D space. Curvature and torsion completely define the shape of a 3-D curve. A scheme is presented that uses the length of this vector, also called the total curvature, for the segmentation of 3-D contours. A quintic B-spline is used in this formulation to obtain the total curvature for noisy data. Examples of nonnoisy and noisy data illustrate the merit of the scheme.