Object tracking is an essential problem in computer vision that has been extensively
researched for decades. Tracking objects in thermal images is particularly difficult because …

In this article, we detect and track visual objects by using Siamese network or twin neural
network. The Siamese network is constructed to classify moving objects based on the …

In remote sensing images, small target size and diverse background cause difficulty in
locating targets accurately and quickly. To address the lack of accuracy and inefficient real …

Unmanned Aerial Vehicle (UAV) has been widely used in military reconnaissance, smart
transportation, public security and other fields. UAV-based person tracking is attracting …

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 …

Multi-object tracking (MOT) is a significant and widespread research field in image
processing and computer vision. The goal of the MOT task consists in predicting the …

Multiple human tracking is a fundamental problem in understanding the context of a visual
scene. Although both accuracy and speed are required in real-world applications, recent …

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 …

Unmanned aerial vehicles (UAVs) have increased the convenience of urban life.
Representing the recent rapid development of drone technology, UAVs have been widely …

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 …