Model-based segmentation and classification of trajectories (Extended abstract)

S.P.A. Alewijnse, K. Buchin, M. Buchin, S. Sijben, M.A. Westenberg

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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 languageEnglish
Title of host publication30th European Workshop on Computational Geometry (EuroCG 2014, Ein-Gedi, Israel, March 3-5, 2014)
Pages1-4
Publication statusPublished - 2014
Event30th European Workshop on Computational Geometry (EuroCG 2014) - Dead Sea, Israel
Duration: 3 Mar 20145 Mar 2014
Conference number: 30
https://www.cs.bgu.ac.il/~eurocg14/

Workshop

Workshop30th European Workshop on Computational Geometry (EuroCG 2014)
Abbreviated titleEuroCG 2014
CountryIsrael
CityDead Sea
Period3/03/145/03/14
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)