Abstract
When detecting ridge-valley lines on 3D mesh model, estimation of the curvature and curvature derivatives may often yields to squiggly and noisy result, because the estimation is sensitive against unwanted surface noises. We present two algorithms to obtain smooth and noiseless ridge-valley lines. First, we apply an iterative procedure on ridge and valley vertices and their previous and next neighbors on connected feature lines, which leads to smooth lines. Secondly, we propose an algorithm to distinguish noises from meaningful feature lines based on graph theory model. Each separate feature line is considered as an undirected weighted graph which is called as Feature Graph. We can reasonably get rid of most noises and preserve meaningful feature lines through optimizing the minimal spanning tree of each feature graph.
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Jing, H., Zhang, W., Zhou, B. (2006). Ridge-Valley Lines Smoothing and Optimizing. In: Pan, Z., Cheok, A., Haller, M., Lau, R.W.H., Saito, H., Liang, R. (eds) Advances in Artificial Reality and Tele-Existence. ICAT 2006. Lecture Notes in Computer Science, vol 4282. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11941354_51
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DOI: https://doi.org/10.1007/11941354_51
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-49776-9
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