The VAT (formerly the large-scale video analytics project), is a research endeavor aimed at establishing a software workbench for video analysis, annotation, and visualization, using both current and experimental discovery methods and built on the Clowder framework/interface. Led by Virginia Kuhn of the USC School of Cinematic Arts – with Alan Craig, Michael Simeone as CoPIs – and supported by the NSF’s XSEDE program (extreme science and engineering discovery environment), the VAT project team includes experts in media studies, computational analysis, computer vision, database formation and humanistic epistemologies.*


View of individual files in the VAT (Clowder) interface.

Filmic media is one of the most compelling big data issues of our time. Its formats are diverse, rapidly transmitted, and boundlessly large in number. As such, it demands scholarly attention beyond the field of cinema studies.

The VAT joins the emergent field of cultural analytics, an approach that deploys computer technologies to analyze the formal features of art and culture, making them available to interpretive methods. Moving image media is particularly ripe for computational analysis given its ubiquity in contemporary culture. Indeed, digital video—whether recorded digitally or digitized from film—is a rapidly expanding form of cultural production, one made possible by the proliferation of personal recording technologies and hosting platforms like YouTube, Vimeo and the Internet Archive.

Yet despite its scale and importance, video remains a daunting object for sustained analysis for reasons that are technological, institutional and conceptual in nature. The VAT’s goal is to fill existing gaps in scholars’ ability to ask cultural questions about filmic archives using computers, while also experimenting with transformative methods in research and analysis. The 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.

The soon to be released VAT gateway will allow early testers to use the VAT. For information or to be included, email:

* The team includes: PI: Virginia Kuhn, Co-PI: Alan Craig, Co-PI: Michael Simeone, Luigi Marini, Dave Bock, Sandeep Puthanveetil, Mona Wong, Lianna Diesendruck, Ritu Arora.
Publications about this project:

THE VAT: Enhanced Video Analysis, Kuhn, et al. July 15, 2015. XSEDE ’15 Proceedings of the 2015 Annual Conference on Extreme Science and Engineering Discovery Environment Article No. 21

MOVIE: Large Scale Automated Analysis of MOVing ImagEs (2014).

Large Scale Video Analytics: On-demand, iterative inquiry for moving image research (2012).

Multiple Concurrent Queries on Demand: Large Scale Video Analysis in a Flash Memory Environment as a case for Humanities Supercomputing (2012).

Press about the project:

Taking video analytics to the next level,” in Federal Computer Week, 5/12/2014 by John Moore.

Extreme scale video image retrieval and research,” in International Science Grid This Week, by Amber Harmon. September 18, 2013.

Visual Literacy,” in Access Magazine, by Barbara Jewett. October 16, 2013.