Creative Commons Attribution 3.0 Unported license
An important task in trajectory analysis is defining a meaningful representative for a cluster of similar trajectories. Formally defining and computing such a representative r is a challenging problem. We propose and discuss two new definitions, both of which use only the geometry of the input trajectories. The definitions are based on the homotopy area as a measure of similarity between two curves, which is a minimum area swept by all possible deformations of one curve into the other. In the first definition we wish to minimize the maximum homotopy area between r and any input trajectory, whereas in the second definition we wish to minimize the sum of the homotopy areas between r and the input trajectories. For both definitions computing an optimal representative is NP-hard. However, for the case of minimizing the sum of the homotopy areas, an optimal representative can be found efficiently in a natural class of restricted inputs, namely, when the arrangement of trajectories forms a directed acyclic graph.
@InProceedings{chambers_et_al:LIPIcs.ESA.2016.27,
author = {Chambers, Erin and Kostitsyna, Irina and L\"{o}ffler, Maarten and Staals, Frank},
title = {{Homotopy Measures for Representative Trajectories}},
booktitle = {24th Annual European Symposium on Algorithms (ESA 2016)},
pages = {27:1--27:17},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-015-6},
ISSN = {1868-8969},
year = {2016},
volume = {57},
editor = {Sankowski, Piotr and Zaroliagis, Christos},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2016.27},
URN = {urn:nbn:de:0030-drops-63783},
doi = {10.4230/LIPIcs.ESA.2016.27},
annote = {Keywords: trajectory analysis, representative trajectory, homotopy area}
}