System and Methods for Detection of Adverse Events
Detecting adverse or anomalous events in a captured video or a live video stream is a challenging task due to the subjective definition of ""anomalous"" as well as the duration of such events. Anomalous events are usually short-lived and occur rarely. We present an unsupervised solution for this problem. Our method is able to capture the video segment where the anomaly happens via the analyses of the interaction between the spatially co-located interest points. The evolution of their motion characteristics is modeled, and abrupt changes are used to temporally segment the videos. Spatiotemporal and motion features are then extracted to model standard events and identify the anomalous segments using a one-class classifier.
Professor, Computer Science