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In this paper, we present a novel method based on clustering for identifying 3D line from point clouds, called “self-organizing fuzzy k-means algorithm”. The algorithm automatically finds the optimal number of cluster and self organizes the clusters based on inter/intra-cluster distances and cluster's performance evaluation. The self-organizing fuzzy k-means is applied in 3D line identification from...
The task of discovering and extracting the geometric features such as points, lines, corners and curves plays an important role in object recognition, 3D modeling, robot mapping and navigation. In this paper, we present an effective 3D line extraction method by using the combined data from 2D images and 3D point clouds. 2D lines are first extracted from 2D image, then are projected back to get the...
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