AUDIO/VISUAL INDEPENDENT COMPONENTS
Paris Smaragdis, Michael A. Casey, Northampton Square · 2003
This paper presents a methodology for extracting meaningful audio/visual features from video streams. We propose a statistical method that does not distinguish between the auditory and visual data, but one that operates on a fused data set. By doing so we discover audio/visual features that correspond to events depicted in the stream. Using these features, we can obtain a segmentation of the input video stream by separating independent auditory and visual events.