Statistical processing of video for detection of events in space and time

Recently, advanced video processing systems have been developed for numerous applications, such as surveillance, tracking, monitoring, object and event detection. The large size of this data and the wide range of detectable events or objects render the automation of various video processing procedures necessary. The proposed system first finds the pixels where activities occur by processing the higher order statistics of luminance changes between accumulated video frames. Once these pixels are extracted, sequential likelihood ratio based change detection techniques are applied to find at which frames activities occur. The resulting system is novel, as it can localize actions both in space and in time, in a theoretically sound manner. Testing takes place with real video sequences, to demonstrate its effectiveness.