Multi-object tracking (MOT) is to simultaneously track multiple targets, eg, pedestrians in this
work, through locating them and maintaining their identities to make their individual …

Based on tracking-by-detection, we propose a hierarchical-matching-based online and real-
time multi-object tracking approach with deep appearance features, which can effectively …

In the recent past, the computer vision community has developed centralized benchmarks
for the performance evaluation of a variety of tasks, including generic object and pedestrian …

Object tracking is a crucial research area within the field of intelligent transportation,
providing a vital foundation for anomalous behavior analysis and traffic statistics. Although …

Multi-object tracking (MOT) is a critical task in various domains, such as traffic analysis,
surveillance, and autonomous vehicles. The joint-detection-and-tracking paradigm has been …

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

Multi-camera multiple people tracking is a crucial technology for surveillance crowd
management and social behavior analysis enabling large-scale monitoring and …

In detection-based multi-object tracking (MOT), one challenging problem is to design a
robust affinity model for data association. Moreover, since these approaches entirely rely on …

Numerous object-tracking and multiple-person-tracking algorithms have been developed in
the field of computer vision, but few trackers can properly address the issue of when a …

Multi-object tracking (MOT) aims at detecting and assigning identities for objects in videos.
Complicated scenes, severe occlusions, irregular motions, and ambiguous appearances of …