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Classifying cinematographic shot types
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AI
DOI：10.1007/s11042-011-0916-9.png)
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Abstract
En 中文
In film-making, the distance from the camera to the subject greatly affects the narrative power of a shot. By the alternate use of Long shots, Medium and Close-ups the director is able to provide emphasis on key passages of the filmed scene. In this work we investigate five different inherent characteristics of single shots which contain indirect information about camera distance, without the need to recover the 3D structure of the scene. Specifically, 2D scene geometric composition, frame colour intensity properties, motion distribution, spectral amplitude and shot content are considered for classifying shots into three main categories. In the experimental phase, we demonstrate the validity of the framework and effectiveness of the proposed descriptors by classifying a significant dataset of movie shots using C4.5 Decision Trees and Support Vector Machines. After comparing the performance of the statistical classifiers using the combined descriptor set, we test the ability of each single feature in distinguishing shot types.
Keywords:
Shot type
Movie content
Feature extraction
Journal
IF:
3
Papers:
1.9W
Citations:
3.2W