In this paper, we use the deep sort multi-target tracking algorithm to achieve multi-target
tracking of pedestrians and vehicles in traffic scenes. In this paper, firstly, yolov4 is used to …

Target detection and tracking are crucial in autonomous driving and intelligent
transportation, especially in pedestrians and traffic safety. The dynamic pedestrian tracking …

Aiming at the problem of insufficient tracking accuracy caused by object occlusion in the
process of multi-object tracking, this paper proposes a multi-order semantic fusion …

Most current online multi-object tracking (MOT) methods include two steps: object detection
and data association, where the data association step relies on both object feature …

Pedestrian multi-object tracking is an important research direction in the fields of computer
vision which has been widely applied in intelligent surveillance, human-computer interaction …

Most multi-object tracking methods have achieved good results in tracking multiple
pedestrians with Kalman filter, but their tracking performance in crowded scenes is still poor …

Multi-object pedestrian tracking plays a crucial role in autonomous driving systems, enabling
accurate perception of the surrounding environment. In this paper, we propose a …

Pedestrians are often vulnerable users of urban roads and ensuring their safety is a
pressing challenge in the filed of intelligent transportation. Multiple pedestrian tracking is …

In the era of rapid technological advancement, the demand for sophisticated Multi-Object
Tracking (MOT) systems in applications such as intelligent surveillance and autonomous …

The existing pedestrian tracking applications are challenging to balance real-time
performance and accuracy. We propose a detection–tracking–correction strategy based on …