### Abstract

We present efficient algorithms for segmenting and classifying a trajectory based on a parameterized movement model like the Brownian bridge movement model. Segmentation is the problem of subdividing a trajectory into parts such that each art is homogeneous in its movement characteristics. We formalize this using the likelihood of the model parameter. We consider the case where a discrete set of m parameter values is given and present an algorithm to compute an optimal segmentation with respect to an information criterion in O(nm) time for a trajectory with n sampling points. Classification is the problem of assigning trajectories to classes. We present an algorithm for discrete classification given a set of trajectories. Our algorithm computes the optimal classification with respect to an information criterion in O(m^2 + mk(log m + log k)) time for m parameter values and k trajectories, assuming bitonic likelihood functions.

Original language | English |
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Title of host publication | 30th European Workshop on Computational Geometry (EuroCG 2014, Ein-Gedi, Israel, March 3-5, 2014) |

Pages | 1-4 |

Publication status | Published - 2014 |

Event | 30th European Workshop on Computational Geometry (EuroCG 2014) - Dead Sea, Israel Duration: 3 Mar 2014 → 5 Mar 2014 Conference number: 30 https://www.cs.bgu.ac.il/~eurocg14/ |

### Workshop

Workshop | 30th European Workshop on Computational Geometry (EuroCG 2014) |
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Abbreviated title | EuroCG 2014 |

Country | Israel |

City | Dead Sea |

Period | 3/03/14 → 5/03/14 |

Internet address |

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## Cite this

Alewijnse, S. P. A., Buchin, K., Buchin, M., Sijben, S., & Westenberg, M. A. (2014). Model-based segmentation and classification of trajectories (Extended abstract). In

*30th European Workshop on Computational Geometry (EuroCG 2014, Ein-Gedi, Israel, March 3-5, 2014)*(pp. 1-4)