Curve skeleton extraction via k-nearest-neighbors based contraction - Zhou, Jianling; Liu, Ji; Zhang, Min (Zielona Góra: Uniwersytet Zielonogórski)
We propose a skeletonization algorithm that is based on an iterative points contraction. We make an observation that the local center that is obtained via optimizing the sum of the distance to k nearest neighbors possesses good properties of robustness to noise and incomplete data. Based on such an observation, we devise a skeletonization algorithm that mainly consists of two stages: points contraction and skeleton nodes connection. Extensive experiments show that our method can work on raw scans of real-world objects and exhibits better robustness than the previous results in terms of extracting topology-preserving curve skeletons.
Keywords: curve skeleton; points contraction; point cloud; k nearest neighbors