Monitoring and surveillance of urban road traffic using low altitude drone images: a deep learning approach

• Published in: Multimedia tools and applications Vol. 81; no. 14; pp. 19683 - 19703
• Main Authors: Gupta, Himanshu, Verma, Om Prakash
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.06.2022; Springer Nature B.V
• Subjects: 1205: Emerging Technologies for Information Hiding and Forensics in Multimedia Systems; Algorithms; Aspect ratio; Computer Communication Networks; Computer Science; Data Structures and Information Theory; Datasets; Deep learning; Incompatibility; Low altitude; Machine learning; Monitoring; Multimedia Information Systems; Object recognition; Special Purpose and Application-Based Systems; Surveillance; Traffic; Traffic accidents; Traffic surveillance; Unmanned aerial vehicles; Deep learning; Traffic surveillance; CNN; UAV; Aerial image; Object detection
• ISSN: 1380-7501; 1573-7721
• DOI: 10.1007/s11042-021-11146-x

In the contemporary era, the global explosion of traffic has created many eye-catching concerns for policymakers. This not only enhances pollution but also leads to several road accident fatalities which may be greatly reduced by proper monitoring and surveillance. Further, with the advent of UAV te...