Abstract
In this paper, we propose a new robust feature extraction algorithm for 3D models based on principal curvature direction. After principal curvatures directional fuzzy filtering, it is a good description of the geometric discontinuity. Compared with of the curvatures value, the impact of noise on the principal curvature direction is small. Therefore, feature extraction based on principal curvature direction is more robust and more accurately. © 2012 Springer-Verlag.
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CITATION STYLE
Li, J. J., & Fan, H. (2012). Robust feature extraction based on principal curvature direction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7633 LNCS, pp. 186–193). https://doi.org/10.1007/978-3-642-34263-9_24
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