Processing video from urban video surveillance cameras requires the use of algorithms for multi-object detection and tracking on video in real-time. However, existing computer vision algorithms require the use of powerful equipment and are not sufficiently optimized to process multiple video streams simultaneously. This article proposes an approach to using the tracker in conjunction with the YoloV4 object detector for real-time video processing on medium-power equipment. Paper also presents the solution for difficulties that arise during work with optical flow. The results of the comparison of the accuracy and speed of image processing of the applied approach with such trackers as IOU17, SORT, KCF, and MOSSEE are also presented.
Real Time Multi Object Detection & Tracking on Urban Cameras
Sustain. Civil Infrastruct.
International Road Federation World Meeting & Exhibition ; 2021 ; Dubai, United Arab Emirates November 07, 2021 - November 10, 2021
2022-04-21
12 pages
Article/Chapter (Book)
Electronic Resource
English
High Precision Real-time 3D Tracking Using Cameras
AIAA | 2011
|High Precision Real-time 3D Tracking Using Cameras
British Library Conference Proceedings | 2011
|Robust real-time pedestrians detection in urban environments with low-resolution cameras
Online Contents | 2014
|