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DEXAW
2002
IEEE

Robust Similarity Measures for Mobile Object Trajectories

14 years 14 days ago
Robust Similarity Measures for Mobile Object Trajectories
We investigate techniques for similarity analysis of spatio-temporal trajectories for mobile objects. Such kind of data may contain a great amount of outliers, which degrades the performance of Euclidean and Time Warping Distance. Therefore, here we propose the use of non-metric distance functions based on the Longest Common Subsequence (LCSS), in conjunction with a sigmoidal matching function. Finally, we compare these new methods to various ÄÔ Norms and also to Time Warping distance (for real and synthetic data) and we present experimental results that validate the accuracy and efficiency of our approach, especially under the strong presence of noise.
Michail Vlachos, Dimitrios Gunopulos, George Kolli
Added 14 Jul 2010
Updated 14 Jul 2010
Type Conference
Year 2002
Where DEXAW
Authors Michail Vlachos, Dimitrios Gunopulos, George Kollios
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