Virginia Kuhn
Michael Simeone
ABSTRACT
In this paper we describe our efforts at establishing a software workbench for video analysis, annotation, and visualization, using both current and experimental discovery methods. This project builds upon our previous research with video and image analysis, and joins the emergent field of cultural analytics in the digital humanities. Moving image media is particularly ripe for computational analysis given its increasing ubiquity in contemporary culture. Hoping to make video more legible as a big data format, we employ visual media in the public domain and we focus on crowd-sourced annotation, aural and visual analysis and visualization of extracted image data. Our goal is to fill in existing gaps for asking cultural questions about video archives using computers, we also experiment with transformative methods in video research and analysis. Our long term goal is to allow researchers to move with agility from textual description and collection management, to manual inspection, to automated analysis, to visualization of discrete films as well as whole collections.
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Index Terms
MOVIE: Large Scale Automated Analysis of MOVing ImagEs
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