We present a new approach for dealing with distribution change and concept drift when learning from data sequences that may vary with time. We use sliding windows whose size, inst...
This paper presents a new scenario recognition algorithm for Video Interpretation. We represent a scenario model with the characters involved in the scenario, with its sub-scenario...
There is a great deal of interest in methods to assess the perceptual quality of a video sequence in a full reference framework. Motion plays an important role in human perception...
Mining repeated patterns in television broadcast is important to advertisers in tracking a large number of television commercials. It can also benefit long-term archival of telev...
In this paper, a framework that combines feature extraction, model learning, and likelihood computation, is presented for video event detection. First, the independent component a...