Abstract
Color plays a fundamental role in film design and production. Unfortunately, existing solutions for film analysis in the digital humanities address perceptual and spatial color information only tangentially. We introduce VIAN, a visual film annotation system centered on the semantic aspects of color film analysis. The tool enables expert-assessed labeling, curation, visualization, and classification of film color features based on their perceived context and aesthetic quality. Crucially, it is also the first of its kind that incorporates foreground-background information as it is made possible by modern deep learning segmentation methods. The proposed visual front-end is seamlessly integrated with a multimedia data management system, so that films can undergo a full color-oriented analysis pipeline by scholars and practitioners.
Halter, Gaudenz