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IDA
2009
Springer

Trajectory Voting and Classification Based on Spatiotemporal Similarity in Moving Object Databases

9 years 11 months ago
Trajectory Voting and Classification Based on Spatiotemporal Similarity in Moving Object Databases
We propose a method for trajectory classification based on trajectory voting in Moving Object Databases (MOD). Trajectory voting is performed based on local trajectory similarity. This is a relatively new topic in the spatial and spatiotemporal database literature with a variety of applications like trajectory summarization, classification, searching and retrieval. In this work, we have used moving object databases in space, acquiring spatiotemporal 3-D trajectories, consisting of the 2-D geographic location and the 1-D time information. Each trajectory is modelled by sequential 3-D line segments. The global voting method is applied for each segment of the trajectory, forming a local trajectory descriptor. By the analysis of this descriptor the representative paths of the trajectory can be detected, that can be used to visualize a MOD. Our experimental results verify that the proposed method efficiently classifies trajectories and their sub-trajectories based on a robust voting method....
Costas Panagiotakis, Nikos Pelekis, Ioannis Kopana
Added 19 Feb 2011
Updated 19 Feb 2011
Type Journal
Year 2009
Where IDA
Authors Costas Panagiotakis, Nikos Pelekis, Ioannis Kopanakis
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