Preserving Topology by a Digitization Process
Journal of Mathematical Imaging and Vision
Multigrid Convergence of Calculated Features in Image Analysis
Journal of Mathematical Imaging and Vision
A Comparative Evaluation of Length Estimators of Digital Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Journal of Mathematical Imaging and Vision
Principal curvatures from the integral invariant viewpoint
Computer Aided Geometric Design
Integral invariants for robust geometry processing
Computer Aided Geometric Design
Normals and curvature estimation for digital surfaces based on convolutions
DGCI'08 Proceedings of the 14th IAPR international conference on Discrete geometry for computer imagery
Binomial convolutions and derivatives estimation from noisy discretizations
DGCI'08 Proceedings of the 14th IAPR international conference on Discrete geometry for computer imagery
Estimation of the derivatives of a digital function with a convergent bounded error
DGCI'11 Proceedings of the 16th IAPR international conference on Discrete geometry for computer imagery
Accurate curvature estimation along digital contours with maximal digital circular arcs
IWCIA'11 Proceedings of the 14th international conference on Combinatorial image analysis
Convergence of binomial-based derivative estimation for C2 noisy discretized curves
Theoretical Computer Science
Convex shapes and convergence speed of discrete tangent estimators
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part II
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In many geometry processing applications, the estimation of differential geometric quantities such as curvature or normal vector field is an essential step. In this paper, we investigate a new class of estimators on digital shape boundaries based on Integral Invariants. More precisely, we provide both proofs of multigrid convergence of curvature estimators and a complete experimental evaluation of their performances.