A survey on trajectory clustering analysis

Understand

This paper comprehensively surveys the development of trajectory clustering.

• Considering the critical role of trajectory data mining in modern intelligent systems for surveillance security, abnormal behavior detection, crowd behavior analysis, and traffic control, trajectory clustering has attracted growing attention.
• Existing trajectory clustering methods can be grouped into three categories: unsupervised, supervised and semi-supervised algorithms.
• In spite of achieving a certain level of development, trajectory clustering is limited in its success by complex conditions such as application scenarios and data dimensions.