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Setting up a Computational Photography Research Studio
Simon Fraser University, 2024
We present a comprehensive framework for a Computational Photography Research Studio, designed to integrate AI-driven methodologies with creative filmmaking. The pipeline includes four key stages (a) Studio Setup and Data Capture, utilizing production cameras and lighting for independent environments; (b) Multicamera Synchronization, ensuring precise temporal alignment across cameras; (c) Camera Calibration, for obtaining accurate 3D representation of our studio; and (d) Green Screen Keying, to isolate the subject for both post-production workflows and computational photography research. Each stage is engineered for flexibility and ease of use in production settings.
Abstract
AI research is transforming creative tasks, with advancements in AI tools rapidly changing post-production expectations. However, the development of these technologies is mostly driven by technologists, often without involving the creatives who will use them. This thesis presents the development of a Computational Photography Research Studio aimed at bridging this gap. The goal is to create a practical and flexible studio setup that allows collaboration between creatives and researchers, allowing production and research to occur simultaneously. This new type of research involves stakeholders, like filmmakers, to ensure the research addresses their needs and benefits creative professionals. The studio setup includes portable production cameras and lighting, enabling the capture of high-quality live-action footage and datasets necessary for developing computational photography algorithms for post-production. This environment aims to direct AI research to better serve the filmmaking community, ultimately enhancing the quality of visual storytelling.
Dissertation
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Video Presentation
BibTeX
author={Obumneme Stanley Dukor},
title={Setting up a Computational Photography Research Studioh},
year={2024},
school={Simon Fraser University},
}