Recent advances in sensor and mobile devices have enabled an unprecedented increase
in the availability and collection of urban trajectory data, thus increasing the demand for …

Trajectory computing is a pivotal domain encompassing trajectory data management and
mining, garnering widespread attention due to its crucial role in various practical …

Tracking devices that can track both players and balls are critical to the performance of
sports teams. Recently, significant effort has been focused on building larger broadcast …

Computing trajectory similarities is a critical and fundamental task for various spatial-
temporal applications, such as clustering, prediction, and anomaly detection. Traditional …

Detecting anomalous trajectory has become an important and fundamental concern in many
real-world applications. However, most of the existing studies 1) cannot handle the …

The increasing demand for analyzing the insights in sports has stimulated a line of
productive studies from a variety of perspectives, eg, health state monitoring, outcome …

Trajectory similarity computation is a core problem in the field of trajectory data queries.
However, the high time complexity of calculating the trajectory similarity has always been a …

Nowadays, it becomes a common practice to capture some data of sports games with
devices such as GPS sensors and cameras and then use the data to perform various …

Forecasting the motion of surrounding obstacles (vehicles, bicycles, pedestrians and etc.)
benefits the on-road motion planning for intelligent and autonomous vehicles. Complex …

Road networks are widely used as a fundamental structure in urban transportation studies.
In recent years, with more research leveraging deep learning to solve conventional …