Fast, high dynamic range light field processing for pattern recognition

Ben Miller, Scott McCloskey

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We present a light field processing method to quickly produce an image for pattern recognition. Unlike processing for aesthetic purposes, our objective is not to produce the best-looking image, but to produce a recognizable image as fast as possible. By leveraging the recognition algorithm's dynamic range and robustness to optical defocus, we develop carefully-chosen tradeoffs to ensure recognition at a much lower level of computational complexity. Capitalizing on the algorithm's dynamic range yields large speedups by minimizing the number of light field views used in refocusing. Robustness to optical defocus allows us to quantize the refocus parameter and minimize the number of interpolations. The resulting joint optimization is performed via dynamic programming to choose the set of views which, when combined, produce a recognizable refocused image in the least possible computing time. We demonstrate the improved recognition dynamic range of barcode scanning using a Lytro camera, and dramatic reductions in computational complexity on a low-power embedded processor.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Computational Photography, ICCP 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467386234
DOIs
StatePublished - 15 Jun 2016
Externally publishedYes
Event2016 IEEE International Conference on Computational Photography, ICCP 2016 - Evanston, United States
Duration: 13 May 201615 May 2016

Publication series

Name2016 IEEE International Conference on Computational Photography, ICCP 2016 - Proceedings

Conference

Conference2016 IEEE International Conference on Computational Photography, ICCP 2016
Country/TerritoryUnited States
CityEvanston
Period13/05/1615/05/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

ASJC Scopus subject areas

  • Media Technology
  • Instrumentation

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