Optical Probing for Analyzing Light Transport

Matthew O'Toole

(Stanford University)

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Date: October 18, 2016


Active illumination techniques enable self-driving cars to detect and avoid hazards, optical microscopes to see deep into volumetric specimens, and light stages to digitally capture the shape and appearance of subjects. These active techniques work by using controllable lights to emit structured illumination patterns into an environment, and sensors to detect and process the light reflected back in response. Although such techniques confer many unique imaging capabilities, they often require long acquisition and processing times, rely on predictive models for the way light interacts with a scene, and cease to function when exposed to bright ambient sunlight.

In this talk, we introduce a generalized form of active illumination—known as optical probing—that provides a user with unprecedented control over which light paths contribute to a photo. The key idea is to project a sequence of illumination patterns onto a scene, while simultaneously using a second sequence of mask patterns to physically block the light received at select sensor pixels. This all-optical technique enables RAW photos to be captured in which specific light paths are blocked, attenuated, or enhanced. We demonstrate experimental probing prototypes with the ability to (1) record live direct-only or indirect-only video streams of a scene, (2) capture the 3D shape of objects in the presence of complex transport properties and strong ambient illumination, and (3) overcome the multi-path interference problem associated with time-of-flight sensors.

Further Information:

Matthew O’Toole is a Banting Postdoctoral Fellow at Stanford’s Computational Imaging group. He received his Ph.D. degree from the University of Toronto in 2016 on research related to active illumination and light transport. He organized the IEEE 2016 International Workshop on Computational Cameras and Displays, and was a visiting student at the MIT Media Lab’s Camera Culture group in 2011. His work was the recipient of two “Best Paper Honorable Mention” awards at CVPR 2014 and ICCV 2007, and two “Best Demo” awards at CVPR 2015 and ICCP 2015.

Created: Wednesday, October 19th, 2016