In this paper, we address various challenges in multi-pedestrian and vehicle tracking in high-
resolution aerial imagery by intensive evaluation of a number of traditional and Deep …

In this paper, we address various challenges in multi-pedestrian and vehicle tracking in high-
resolution aerial imagery by intensive evaluation of a number of traditional and Deep …

Multi-pedestrian tracking in aerial imagery has several applications such as large-scale
event monitoring, disaster management, search-and-rescue missions, and as input into …

Multi-object tracking is a vital component in various robotics and computer vision
applications. However, existing multi-object tracking techniques trade off computation …

In this paper, we extend the discriminant correlation filter (DCF) based deep learning tracker
to multi-object tracking. For each object, we use an individual tracker to estimate the …

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 …

Tracking multiple pedestrians across multi-camera scenarios is an important part of
intelligent video surveillance and has great potential application for public security, which …

Multi-pedestrian tracking (MPT) on the road is closely related to a reduction in the possibility
of pedestrian-vehicle collisions when using advanced driver assistance systems. Therefore …

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 …

Multi-object tracking aims to estimate the complete trajectories of objects in a scene.
Distinguishing among objects efficiently and correctly in complex environments is a …