Android Eye Crime (violence ) detection app

In this project, we describe how to detect anomalies activities taking place in an outdoor surveillance environment. Human tracks are provided in real time by the baseline video surveillance system. Given trajectory information, the event analysis module will attempt to determine whether or not a suspicious activity is currently being observed. However, due to real-time processing constrains, there might be false alarms generated by video image noise or non-human objects. 

It requires further intensive examination to filter out false event detections which can be processed in an off-line fashion. We propose a system to automate the task of analyzing video surveillance. In low level task, a trajectory-based method processes trajectory data and detects abnormal events in real time. In high level task, an intensive video analysis algorithm checks whether the detected abnormal event is triggered or not.

Keywords: Video Analysis, Android, Eye Detection, Abnormal Events.