An Innovative Tempo Model for Movie Content Analysis
The paper presents a novel tempo model for movie content analysis. We originally propose that tempo indicates the rhythm of both movie scenarios and human perception and focus on the low level features extraction to represent both aspects. By thoroughly analyzing them, we classify the factors of tempo into two sorts. The first is based on the film grammar and we use the low level features of shot length and camera motion to describe filmmaking by directors. The second is based on the human perception and the low level features of motion intensity, motion complexity, audio energy and audio pace are integrated for the formulation of information to describe the viewers' emotional changes to continuously developing storyline. With both factors, tempo is defined and tempo flow plot is derived as the clue of storyline. Then we implement the tempo model for Action scene detection and build a system, SmartMovirPlayer, for hierarchical browse and edit with action concept annotation. The large-scale experiments demonstrate the effectiveness of the tempo model for movie content analysis.