关键词: 边界点, 非均匀简化, 散乱点云, kd-树

Abstract: A non-uniform simplification approach with boundary points reservation was proposed concerning the boundary points loss caused by most point cloud simplification algorithms. First, kd-tree was used to represent the spatial topology relationship of the scattered point cloud and to calculate the k-nearest neighbors for each data point. Then an improved algorithm for boundary points detection of point cloud was presented to solve the low efficiency when the current algorithms extract boundary according to uniform distribution of point cloud. Consequently, all the resulted boundary points were reserved, while the non-boundary points were reserved for final non-uniform simplification according to the surface variation and their nearest neighbors. The experimental result shows that the proposed simplification approach has high accuracy and low space complexity, and can reserve the boundary points.

Key words: boundary point, non-uniform simplification, scattered point cloud, kd-tree