Route Restoring Based on Hidden Semi-Markov Model

DOI

10.2991/icfcce-14.2014.29How to use a DOI?

Keywords

Geo-tagged Photo, Hot spot, Travel route, Route restoring, Trajectory mining

Abstract

Present raw geo-tagged photo routes cannot provide information as enough as complete GPS trajectories due to the defects hidden in them. This paper mainly aims at analyzing the large amounts of geo-tagged photos and proposing a novel travel route restoring method. In our approach we apply the Hidden Semi- Markov model and Mean Value method to demonstrate migration discipline in the hot spots and restore the significant region sequence into complete GPS trajectory. At the end of the paper, a novel experiment method is designed to demonstrate that the approach is feasible in restoring route, and there is a good performance.

Copyright

© 2014, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Guannan Wang
AU  - Jian Ye
AU  - Zhenmin Zhu
PY  - 2014/03
DA  - 2014/03
TI  - Route Restoring Based on Hidden Semi-Markov Model
BT  - Proceedings of the 2014 International Conference on Future Computer and Communication Engineering
PB  - Atlantis Press
SP  - 120
EP  - 123
SN  - 1951-6851
UR  - https://doi.org/10.2991/icfcce-14.2014.29
DO  - 10.2991/icfcce-14.2014.29
ID  - Wang2014/03
ER  -