Object Detection in Traffic Videos: A Survey

Document Type

Article

Publication Date

7-1-2023

Abstract

Traffic video analytics has become one of the core components in the evolution of transportation systems. Artificially intelligent traffic management systems apply computer vision techniques to alleviate the monotony of manually monitoring the video feeds from surveillance cameras. Object detection is the most important step in these systems, and much research has been done on identifying objects in traffic scenes. This paper reviews various algorithms used for object detection in traffic surveillance, in addition to the recent trends and future directions. Based on the approaches used in the related studies, the object detection methods are categorized into motion-based and appearance-based techniques. Each group of techniques is further classified into a number of subcategories and the advantages and disadvantages of each method are finally analyzed. The major challenges, limitations, and potential solutions are also discussed along with the future directions.

Identifier

85153376280 (Scopus)

Publication Title

IEEE Transactions on Intelligent Transportation Systems

External Full Text Location

https://doi.org/10.1109/TITS.2023.3258683

e-ISSN

15580016

ISSN

15249050

First Page

6780

Last Page

6799

Issue

7

Volume

24

This document is currently not available here.

Share

COinS