A framework of moving behavior modeling in the maritime surveillance

Po Ruey Lei, Ing Jiunn Su, Wen-Chih Peng, Wei Yu Han, Chien Ping Chang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Due to requirements of homeland security, maritime traffic surveillance becomes an important research area. An automated solution to analyze the collected data and summarize them into a model is helpful for objects' movement behavior analysis in maritime domain. However, it is a challenging problem to develop a model that can precisely capture the objects' movement behavior due to objects would seldom exactly repeat the same moving path in the maritime space, a free moving space. In this paper, based on multiple vessels' trajectories from Automatic Identification System (AIS), we aim to mine trajectory patterns and profile them into a model, called TMP model (Trajectory Pattern Mining and Profiling model). We conduct experiments on real data and experimental results demonstrate that TMP model can effectively and precisely reflect the movement behaviors in the maritime surveillance.

Original languageEnglish
Pages (from-to)33-44
Number of pages12
JournalChung Cheng Ling Hsueh Pao/Journal of Chung Cheng Institute of Technology
Volume40
Issue number2
StatePublished - 1 Nov 2011

Keywords

  • Moving behavior
  • Trajectory
  • Trajectory pattern mining

Fingerprint Dive into the research topics of 'A framework of moving behavior modeling in the maritime surveillance'. Together they form a unique fingerprint.

Cite this