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Salient Critical Points for Meshes by Yu-Shen Liu; Min Liu; Daisuke Kihara; Karthik Ramani is a scholarly article available to read on EtoBox.

What is Salient Critical Points for Meshes about?

a) (b) (c) (d) Figure 1: Salient critical points (the blue, red, and green points are minimum, maximum, and saddles, respectively). (a) The back of the lion head model with large noise and small hair textures, and the corresponding mean curvature visualization. (b) The mean curvature function yields 7,629 critical points due to the curvature function's sensitivity to noise. (c) The corresponding mesh saliency. (d) Salient critical points with lower number. Since mesh saliency in (c) captures the hair texture and negates the noisy curvature in (a), our method based on saliency selects the more interesting critical points in the important region. In color images shown in this paper, warmer colors (reds and yellows) show high curvature or saliency and cooler colors (blues) show low curvature or saliency.

Author

Yu-Shen Liu; Min Liu; Daisuke Kihara; Karthik Ramani

Publisher

ACM

Published

2007

Language

EN