Positional data in team sports is key in evaluating the players' individual and collective
performances. When the sole source of data is a broadcast-like video of the game, an …

Abstract Multi-camera Multi-Object Tracking has drawn significant attention in recent years
due to its critical role in surveillance analytics and related fields. Various challenges …

Re-identification (ReID) in multi-object tracking (MOT) for UAVs in maritime computer vision
has been challenging for several reasons. More specifically, short-term re-identification …

Performance analyses based on videos are commonly used by coaches of athletes in
various sports disciplines. In individual sports, these analyses mainly comprise the body …

Deep learning-based object detectors have driven notable progress in multi-object tracking
algorithms. Yet, current tracking methods mainly focus on simple, regular motion patterns in …

Multi-camera multiple people tracking has become an increasingly important area of
research due to the growing demand for accurate and efficient indoor people tracking …

In the field of multi-object tracking (MOT), traditional methods often rely on the Kalman Filter
for motion prediction, leveraging its strengths in linear motion scenarios. However, the …

Multi-target multi-camera tracking (MTMCT) of vehicles, ie tracking vehicles across multiple
cameras, is a crucial application for the development of smart city and intelligent traffic …

The aim of in-trawl catch monitoring for use in fishing operations is to detect, track and
classify fish targets in real-time from video footage. Information gathered could be used to …

Visual tracking and attribute estimation related to age or gender information of multiple
person entities in a scene are mature research topics with the advent of deep learning …