Multi-object tracking (MOT) aims at estimating bounding boxes and identities of objects in
videos. Most methods obtain identities by associating detection boxes whose scores are …

Abstract Multiple Object Tracking (MOT) has emerged as a hot issue in the field of computer
vision recently. MOT has academic and commercial potential in urban public security …

Kalman filter (KF) based methods for multi-object tracking (MOT) make an assumption that
objects move linearly. While this assumption is acceptable for very short periods of …

The challenging task of multi-object tracking (MOT) requires simultaneous reasoning about
track initialization, identity, and spatio-temporal trajectories. We formulate this task as a …

Multiple object tracking gained a lot of interest from researchers in recent years, and it has
become one of the trending problems in computer vision, especially with the recent …

In the realm of video object tracking auxiliary modalities such as depth thermal or event data
have emerged as valuable assets to complement the RGB trackers. In practice most existing …

Multi-person tracking is often solved with a tracking-by-detection approach that matches all
tracks and detections simultaneously based on a distance matrix. In crowded scenes …

Occlusion between different objects is a typical challenge in Multi-Object Tracking (MOT),
which often leads to inferior tracking results due to the missing detected objects. The …

Abstract Recently, Multiple Object Tracking has achieved great success, which consists of
object detection, feature embedding, and identity association. Existing methods apply the …

For an intelligent transportation system, multiple object tracking (MOT) is more challenging
from the traditional static surveillance camera to mobile devices of the Internet of Things …