Publication

Abstract : Event detection in videos is becoming an emerging area of research now a day. Monitoring of people activities using a surveillance camera is an essential one in a recent lifestyle for safety and security. The surveillance cameras are used in a wide variety of places such as in public places, Hospitals, Schools, and Homes for the beneficiaries of common people, patients, children and the elderly. In case of any emergency or abnormal events, immediate notification should be given to the respective people. The abnormal events are recognized from the videos using deep architectures. The goal of event detection in videos is to detect simple and complex actions in real-time data. This has a lot of attention in real-time ambient assisted living environments especially for elder people who live alone in the home. In this paper, a deep architecture of long short term memory recurrent network is proposed to detect fall actions in video inputs..