“…Similar results hold in 3D, γ = 1 is the general case (e.g. see [11]) while γ = 243 158 for smoother boundary [7]. In fact, preceding equations hold whenever the shape boundary can be decomposed in a finite number of convex pieces [9].…”
Section: Area or Volume Estimation By Countingmentioning
Abstract. 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.
“…Similar results hold in 3D, γ = 1 is the general case (e.g. see [11]) while γ = 243 158 for smoother boundary [7]. In fact, preceding equations hold whenever the shape boundary can be decomposed in a finite number of convex pieces [9].…”
Section: Area or Volume Estimation By Countingmentioning
Abstract. 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.
“…where Re(a) = a 0 is the real part and Im(a) := (a 1 , a 2 , a 3 , a 4 , a 5 , a 6 , a 7 ) is the imaginary part of the octave a = (a 0 , a 1 , a 2 , a 3 , a 4 , a 5 , a 6 , a 7 ), and | · | is the Euclidean norm.…”
Section: Introduction and Statement Of The Main Resultsmentioning
confidence: 99%
“…It is plain that 4 √ X and |v| ≤ η(X; |u|), and that E 6 (X; u, v) = ∅ otherwise. By applying (3.3) and (3.6) for n = 6, and (2.1) we derive…”
“…see [38] where µ 0 = 38 25 − , or [39], Theorem 1, where µ 0 = 66 43 − ). We wish to apply this formula to the set A = B R (x) ∩ X, whose size decreases with h. Big "O" notation in Eq.…”
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.
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