Non-refractive modulators for encoding and capturing scene appearance and depth

Ashok Veeraraghavan*, Amit Agrawal, Ramesh Raskar, Ankit Mohan, Jack Tumblin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Scopus citations

Abstract

We analyze the modulation of a light field via non-refracting attenuators. In the most general case, any desired modulation can be achieved with attenuators having four degrees of freedom in ray-space. We motivate the discussion with a universal 4D ray modulator (ray-filter) which can attenuate the intensity of each ray independently. We describe operation of such a fantasy ray-filter in the context of altering the 4D light field incident on a 2D camera sensor. Ray-filters are difficult to realize in practice but we can achieve reversible encoding for light field capture using patterned attenuating mask. Two mask-based designs are analyzed in this framework. The first design closely mimics the angle-dependent ray-sorting possible with the ray filter. The second design [17] exploits frequency-domain modulation to achieve a more efficient encoding. We extend these designs for optimal sampling of light field by matching the modulation function to the specific shape of the band-limit frequency transform of light field. We also show how a hand-held version of an attenuator based light field camera can be built using a medium-format digital camera and an inexpensive mask.

Original languageEnglish (US)
Title of host publication26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
DOIs
StatePublished - 2008
Event26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR - Anchorage, AK, United States
Duration: Jun 23 2008Jun 28 2008

Publication series

Name26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR

Other

Other26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
Country/TerritoryUnited States
CityAnchorage, AK
Period6/23/086/28/08

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Control and Systems Engineering

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