A Unified Memory-Based Approach to 
Cut, Dissolve, Key Frame, and Scene Analysis

Aya Aner and John R. Kender
Department of Computer Science
Columbia University
New York, NY 10027

ABSTRACT 

We review a memory-based buffer model of visual perception, that combines the
lower and middle stages in the analysis of video.  This model was originally
developed for the detection of breaks between physical scene changes ("story
units").  In this paper we show how this method can also be applied for shot
detection.  Moreover, it gives rise to a unified approach for detecting cuts
and gradual changes.  Additionally, as a straightforward corollary to its
definition, it leads to a more natural definition of key frames.  We derive
the theoretic performance of the model, given arbitrary measures of
frame-to-frame dissimilarity.  We show several examples of its response, using
standard color histogram differencing (with the L1 norm as measure).  We
evaluate the model's performance in detecting cuts and dissolves against a
complete hand-segmented situation comedy.