“Making the Invisible Visible: Within Our Bodies, the World Around Us and Beyond,” a Keynote Presentation from the MIT Media Lab

Ramesh Raskar, Associate Professor in the MIT Media Lab, presents the "Making the Invisible Visible: Within Our Bodies, the World Around Us and Beyond" tutorial at the May 2019 Embedded Vision Summit. For more information, please see http://cameraculture.media.mit.edu, http://www.media.mit.edu/~raskar and https://professional.mit.edu/programs/short-programs/advances-imaging.

The invention of X-ray imaging enabled us to see inside our bodies. The invention of thermal infrared imaging enabled us to depict heat. So, over the last few centuries, the key to making the invisible visible was recording with new slices of electromagnetic spectrum. But the impossible photos of tomorrow won’t be recorded; they’ll be computed.

Ramesh Raskar’s group has pioneered the field of femto-photography, which uses a high-speed camera that enables visualizing the world at nearly a trillion frames per second so that we can create slow-motion movies of light in flight. These techniques enable the seemingly impossible: seeing around corners, seeing through fog as if it were a sunny day and detecting circulating tumor cells with a device resembling a blood-pressure cuff.

Raskar and his colleagues in the Camera Culture Group at the MIT Media Lab have advanced fundamental techniques and have pioneered new imaging and computer vision applications. Their work centers on the co-design of novel imaging hardware and machine learning algorithms, including techniques for the automated design of deep neural networks. Many of Raskar’s projects address healthcare, such as EyeNetra, a start-up that extends the capabilities of smart phones to enable low-cost eye exams.

In his keynote presentation, Raskar shares highlights of his group’s work, and his unique perspective on the future of imaging, machine learning and computer vision.

Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.



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