@inproceedings{dc06324935024274aa4bf00e46f53532,
title = "Directional analysis of trajectories based on trajectory smoothing",
abstract = "In this article we propose a framework to discover interesting directional patterns in trajectory data sets. The proposed framework has five stages; trajectory smoothing, directional segmentation, directional classification, filtering and finally clustering. The main contributions are in the stages for smoothing, directional classification and filtering. Trajectory smoothing is an important step in the analysis of complex, non-smooth trajectories data sets, such as animal movement data. In directional classification stage, different subtrajectories are assigned to the classes corresponding to their directional orientation. In the filtration stage the outlier trajectories are removed from the respective classes using a novel convex hull based approach. We used animal movement data in this work.",
keywords = "Clustering, Spatio-temporal, Trajectory",
author = "Tripathi, \{Praveen Kumar\} and Madhuri Debnath and Ramez Elmasri",
note = "Publisher Copyright: {\textcopyright} 2015 ACM.; 5th International Workshop on Mobile Entity Localization and Tracking in GPS-Less Environments, MELT 2015 ; Conference date: 03-11-2015",
year = "2015",
month = nov,
day = "3",
doi = "10.1145/2830571.2830771",
language = "English",
series = "Proceedings of the 5th International Workshop on Mobile Entity Localization and Tracking in GPS-Less Environments, MELT 2015",
publisher = "Association for Computing Machinery, Inc",
editor = "Ying Zhang and Bodhi Priyantha",
booktitle = "Proceedings of the 5th International Workshop on Mobile Entity Localization and Tracking in GPS-Less Environments, MELT 2015",
}