ABSTRACT
ABSTRACT

The data driven, bottom up approach to video segmentation has ignored the inherent structure that exists in video. This work uses the model driven approach to digital video seg- mentation. Mathematical models of video based on video production techniques are formulated. These models are used to classify the edit effects used in video and film pro- duction. The classes and models are used to systematically design the feature detectors for detecting edit effects in digi- tal video. Digital video segmentation is formulated as a fea- ture based classification problem. Experimental results from segmenting cable television programming with cuts, fades, dissolves and page translate edits are presented.