A stylistic device frequently employed by filmmakers
is the synchronous montage (composition) of audio and visual elements.
Synchronous montage helps to increase tension and tempo
in a scene and highlights important events in the story. Sequences
with synchronous montage usually contain rich semantics which
is relevant for understanding a movie. This property is currently
not exploited in automated indexing, annotation, and summarization
of movies. We propose a cross-modal approach that
extracts sequences from a movie with synchronous audio-visual
montage. Experiments confirm that the extracted sequences have
high semantic relevance. Consequently, they represent a useful
basis for different high-level movie abstraction tasks such as
automated movie annotation and movie summarization.