Abstract The AI City Challenge's seventh edition emphasizes two domains at the intersection
of computer vision and artificial intelligence-retail business and Intelligent Traffic Systems …

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 …

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 …

We present a robust multi-camera gymnast tracking, which has been applied at international
gymnastics championships for gymnastics judging. Despite considerable progress in multi …

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 …

Traditional palm oil production methods for evaluating fruit bunches (FFBs) are inefficient,
costly, and have limited coverage. This study evaluates the performance of various YOLO …

Multi-object tracking in sports scenarios has become one of the focal points in computer
vision, experiencing significant advancements through the integration of deep learning …

Multi-view pedestrian tracking has frequently been used to cope with the challenges of
occlusion and limited fields-of-view in single-view tracking. However, there are few end-to …

Multi-camera people tracking (MCPT) has become increasingly relevant in recent years as
the demand for accurate people-tracking systems has increased along with the growing …

Assessing gross motor development in toddlers is crucial for understanding their physical
development and identifying potential developmental delays or disorders. However, existing …