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 …

After several years of development, the multi-target tracking algorithm has significantly
transitioned from being researched to being put into practical production and life. The …

Multi-Object tracking in video processing is a challenging task in computer vision. Typically,
tracking the objects in a video is performed using binocular vision or top-down camera …

Multi-object tracking is a very popular research area in computer vision, and detection-
based tracking is one of the commonly used methods. In this paper, we analyze tracking of …

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

Multiple-object tracking is a fundamental computer vision task which is gaining increasing
attention due to its academic and commercial potential. Multiple-object detection …

With the continuous development of deep learning in multi-target tracking, the use of
convolutional neural network for feature extraction has replaced the traditional feature …

Pedestrian target tracking is an important problem in the field of computer vision. To address
low tracking accuracy and tracking errors in pedestrian target tracking. This paper …

With the shortcomings of traditional algorithm in video surveillance on low accuracy, poor
robustness and unable achieved real-time tracking for multi-targets, this paper presents a …

Multiple object tracking (MOT) in urban traffic is exciting since there is large variation of road
user appearance. In order to overcome that variation while tracking the objects, a deep …