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Fast and Efficient Kinetic Spanners

Joint project with Domagoj Matijevic at University J.J. Strossmayer in Osijek. Funded by the German Academic Exchange Service

Point cloud data in low dimensional Euclidean spaces (dimensions up to ten) arises in many applications either through measurements or simulations. For analysis, e.g., clustering or near neighbor search, such data often need to be organized into a data structure. A popular data structure to that means is a kinetic (1+epsilon)-spanner. In this project we want to analyze and implement different point cloud filtrations since point cloud filtrations have been used as a key ingredient of in the construction of succinct, efficient kinetic spanners.