Detecting topical events in digital video

Abstract

The detection of events is essential to high-level semantic querying of video databases. It is also a very challenging problem requiring the detection and integration of evidence for an event available in multiple information modalities, such as audio, video and language. This paper focuses on the detection of specific types of events, namely, topic of discussion events that occur in classroom/lecture environments. Specifically, we present a query-driven approach to the detection of topic of discussion events with foils used in a lecture as a way to convey a topic. In particular, we use the image content of foils to detect visual events in which the foil is displayed and captured in the video stream. The recognition of a foil in video frames exploits the color and spatial layout of regions on foils using a technique called region hashing. Next, we use the textual phrases listed on a foil as an indication of a topic, and detect topical audio events as places in the audio track where the best evidence for the topical phrases was heard. Finally, we use a probabilistic model of event likelihood to combine the results of visual and audio avent detection that exploits their time cooccurrence. The resulting identification of topical events is evaluated in the domain of classroom lectures and talks.