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Revealing Underlying Structure and Behaviour from Movement Data

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2012

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Springer

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Spatio-temporal trajectories contain implicit knowledge about the movement of individuals, which is relevant for problems in various domains, e.g. animal migration, traffic analysis, security. In this paper we present real-time approaches to segment trajectories into meaningful parts which reflect the underlying typical behaviour or structure. Based on this information atypical behaviour can be identified.

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Sester, Monika; Feuerhake, Udo; Kuntzsch, Colin; Zhang, Lijuan (2012): Revealing Underlying Structure and Behaviour from Movement Data. KI - Künstliche Intelligenz: Vol. 26, No. 3. Springer. PISSN: 1610-1987. pp. 223-231

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