PhaseCam3D - Learning Phase Masks for Passive Single View Depth Estimation

There is an increasing need for passive 3D scanning in many applications that have stringent energy constraints. In this paper, we present an approach for single frame, single viewpoint, passive 3D imaging using a phase mask at the aperture plane of a camera. Our approach relies on an end-to-end opt...

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Bibliographic Details
Published inIEEE International Conference on Computational Photography pp. 1 - 12
Main Authors Yicheng Wu, Boominathan, Vivek, Huaijin Chen, Sankaranarayanan, Aswin, Veeraraghavan, Ashok
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2019
Subjects
Apertures
Cameras
coded aperture
computational photography
Estimation
Image reconstruction
Optical imaging
passive depth estimation
phase masks
Three-dimensional displays
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Summary:There is an increasing need for passive 3D scanning in many applications that have stringent energy constraints. In this paper, we present an approach for single frame, single viewpoint, passive 3D imaging using a phase mask at the aperture plane of a camera. Our approach relies on an end-to-end optimization framework to jointly learn the optimal phase mask and the reconstruction algorithm that allows an accurate estimation of range image from captured data. Using our optimization framework, we design a new phase mask that performs significantly better than existing approaches. We build a prototype by inserting a phase mask fabricated using photolithography into the aperture plane of a conventional camera and show compelling performance in 3D imaging.
ISSN:2472-7636
DOI:10.1109/ICCPHOT.2019.8747330