Publication Type : Conference Paper
Publisher : International Conference of Soft Computing and Signal Processing
Url : https://link.springer.com/chapter/10.1007/978-981-33-6912-2_24
Keywords : Video surveillance, Deep learning, Suspicious behavior, Face recognition
Campus : Bengaluru
School : School of Engineering
Department : Computer Science
Year : 2021
Abstract : Technologies are advanced an excessive amount when artificial intelligence and computer vision come into the picture. Currently, closed circuit television cameras are used in private and public places for security reasons. The proposed system works as an automatic video closed circuit television to detect suspicious or normal behavior. If any suspicious event happens, the system identifies the person involved in it and warns the authority with a text message. The SMS includes suspicious behavior, identity of person, and closed circuit television camera location. Deep learning is employed to detect normal or suspicious event in a campus area. Once the suspicious activity is identified, the person involved in the activity is identified using the face recognition techniques and the location of the camera is extracted from the text details obtained from the surveillance videos.
Cite this Research Publication : Amrutha, C.V., Jyotsna, C. (2021). A Robust System for Video Classification: Identification and Tracking of Suspicious Individuals from Surveillance Videos. In: Reddy, V.S., Prasad, V.K., Wang, J., Reddy, K.T.V. (eds) Soft Computing and Signal Processing. Advances in Intelligent Systems and Computing, vol 1325. Springer, Singapore. https://doi.org/10.1007/978-981-33-6912-2_24