Multi-object tracking in video surveillance is subjected to illumination variation, blurring,
motion, and similarity variations during the identification process in real-world practice. The …

Pedestrian tracking is an important aspect of autonomous vehicles environment perception
in a vehicle running environment. The performance of the existing pedestrian tracking …

In recent years, several methods and datasets have been proposed to push the performance
of pedestrian detection in crowded scenarios. In this study, three crowd-specific detectors …

The performance of pedestrian multiple object tracking (MOT), which is based on the
tracking-by-detection framework, is exceedingly susceptible to the quality of detection …

Traffic target tracking is a core task in intelligent transportation system because it is useful for
scene understanding and vehicle autonomous driving. Most state‐of‐the‐art (SOTA) …

Multi-object tracking (MOT) is mainly used for detecting and tracking the object on multi-
cameras, which is widely applied in intelligent video surveillance and intelligent security …

There are sub-classes of pedestrians that can be defined and it is important to distinguish
between them for the detection in autonomous vehicle applications, such as elderly, and …

An effective understanding of the environment and accurate trajectory prediction of
surrounding dynamic obstacles are indispensable for intelligent mobile systems (eg …

Multi-object Tracking is an important issue that has been widely investigated in computer
vision. However, in practical applications, moving targets are often occluded due to complex …

Pedestrian trajectory tracking is crucial to ensure pedestrian safety in autonomous driving.
Recently developed multi-sensor based multi-target tracking algorithms either overrely on …