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Learning Depth from Transmissive Diffraction Mask based Sensor
Most cameras today, take photographs by measuring the amount of light in a scene. This means that they discard any information about the directionality of light, which results in a two-dimensional representation of the three-dimensional scene. We have developed a new type of camera that can detect the direction of light as well as image intensity. The 3D scene can be estimated by leveraging this additional information. Due to our manufacturing constraints, the signal from our camera is not ideal, hence the reconstruction process is not straightforward. During this internship, we will investigate machine learning based approaches to compute depth from the information captured by our camera.
Faculty Supervisor:
Michael Langer
Student:
Partner:
Airy3D Inc
Discipline:
Computer science
Sector:
Professional, scientific and technical services
University:
McGill University
Program:
Accelerate
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Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.