Programs
- M. Tech. in Automotive Engineering -
- Clinical Fellowship in Laboratory Genetics & Genomics - Fellowship
Publication Type : Journal Article
Publisher : International Journal of Emerging Technologies and Innovative Research
Source : International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 5, page no.75-79, May-2020
Url : https://www.jetir.org/view?paper=JETIRDV06018
Campus : Chennai
School : School of Engineering
Department : Computer Science
Year : 2020
Abstract : Recently, the utilization of security cameras for crime prevention and early detection of emergencies worldwide has been increased. The expansion in the use of surveillance cameras has aided in crime detection, captures and crime prevention. However, in many cases, it will be recognized and resolved after the occurrence of the crime and concerning continuous surveillance, the weight on the surveillance side is overwhelming and there are situations where suspicious activity may go unnoticed. To overcome this obstacle, a surveillance system that employs Human Activity Recognition techniques which can efficiently decide if the objective individual is an ordinary individual or a suspicious individual can be deployed. It is likewise expected that establishing detection systems can act as a hindrance against crime. This paper proposes a surveillance system that utilizes YOLO and ResNet for detecting suspicious individuals and activities.
Cite this Research Publication : S. Adarsh, Giridhar Kannan, S. Poorvaja, B. S. Vidhyasagar, and J. Arunnehru "Suspicious Activity Detection and Tracking In Surveillance Videos ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 5, page no.75-79, May-2020.