A Heuristic Coordinate Filtering Scheme to Aid Online Indexing of Spatio-Temporal Trajectories

Traditional online indexing of spatio-temporal trajectories requires indexing coordinates at fixed intervals or each time the moving object changes direction or velocity. We propose a heuristic coordinate filtering scheme to help evaluate each periodically sampled coordinate candidacy for indexing. Successful coordinates are the minimum trajectory's coordinates required as control points during the cubic spline interpolation process; invoked whenever a spatio-temporal historical query is made on the indexed trajectory. Using our heuristic coordinate filtering scheme, the number of indexed coordinates is significantly reduced to 25% - 35% of the original amount required by the traditional indexing methods, yet the indexed trajectory's integrity is well preserved. Both heuristic coordinate filtering and cubic spline interpolation step require minimal time penalty, hence allowing our method for online uses.