Automatic trajectory processing has multiple applications, mainly due to the wide availability
of the data. Trajectory data have a significant practical value, making possible the modeling …

Without ground-truth data, trajectory anomaly detection is a hard work and the result lacks of
interpretability. Moreover, in most current methods, trajectories are represented by geometric …

This paper aims to solve two enduring challenges in existing trajectory similarity measures:
computational inefficiency and the absence of the 'uniqueness' property that should be …

In this paper, we propose a new technique to enhance the trajectory shape analysis by
explicitly considering the speed attribute of trajectory data, as an effective and efficient way …

Anomalous trajectory detection which plays an important role in taxi fraud detection and
trajectory data preprocessing is a crucial task in trajectory mining fields. Traditional …

Anomaly detection of trajectory data is important and challenging in many real applications.
Many anomalous trajectory detection algorithms have been developed, however most of …

The detection of abnormal events is a major challenge in video surveillance systems. In
most of the cases, it is based on the analysis of the trajectories of moving objects in a …

The task of detecting anomalous data patterns is as important in practical applications as
challenging. In the context of spatial data, recognition of unexpected trajectories brings …

This paper presents an analysis on Automatic Identification System (AIS) real world ship
data to build a system with the capability to extract useful information for an anomaly …

Existing measures and representations for trajectories have two longstanding fundamental
shortcomings, ie, they are computationally expensive and they can not guarantee …