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Matt Hirsch Dissertation Defense: Computational Visual Reality

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Henry Holtzman
Matt Hirsch

It is not so far-fetched that in the near future, a student will work through a difficult vector calculus problem by using his hands to manipulate a 3D visualization that floats above his desk. A doctor will prepare for heart surgery by practicing on a photo-real replica of his patient's organ. A visitor to the British Museum in London will sketch a golden Pharaoh’s headdress, illuminated by sunlight that pours in the window, never aware that the artifact is still in Egypt. To create more realistic and interactive visual information, displays will need to show high quality 3D images that respond to environmental lighting conditions and user input. The availability of displays capable of addressing the full range of visual experience will improve our ability to interact with computation, the world, and one another. Two of the many problems that have impeded previous efforts to design high-dimensional displays are a) the need to process large amounts of information in real-time, and b) the need to fabricate hardware capable of conveying that information. By applying compressive techniques that take advantage of multiple data redundancies in light transport, it is possible to overcome the data challenges of light field display and capture, and make use of hardware available in the near-term. In this thesis Hirsch proposes display and capture frameworks that use non-negative tensor factorization and dictionary-based sparse reconstruction, respectively, in conjunction with the co-design of algorithms, optics, and electronics to allow compressive, simultaneous, light field display and capture.

Additional Featured Research By

(Unpublished) Information Ecology

Host/Chair: Henry Holtzman

Participant(s)/Committee

Ramesh Raskar, V. Michael Bove, Michael Hawley

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