A framework of spatio-temporal trajectory simplification methods

We present an extensible, generic, spatio-temporal trajectory simplification framework that modularises trajectory simplification into the stages of normalising, ranking, and reduction. We combine a range of ranking strategies and scoring heuristics - some from the literature and some new - into our framework modules and create a variety of spatio-temporal trajectory simplification methods. These trajectory simplification methods are experimented upon using real world and synthetic datasets, measuring running time, geometric displacement, and region-of-interest visitation. The results indicate that our proposed framework creates a number of efficient and effective spatio-temporal trajectory simplification methods.