Direct differential range estimation using optical masks

Eero P. Simoncelli, Hany Farid

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

Abstract

We describe a novel formulation of the range recovery problem, based on computation of the differential variation in image intensities with respect to changes in camera position. The method uses a single stationary camera and a pair of calibrated optical masks to directly measure this differential quantity. The subsequent computation of the range image is simple and should be suitable for real-time implementation. We also describe a variant of this technique, based on direct measurement of the differential change in image intensities with respect to aperture size. These methods are comparable in accuracy to other single-lens ranging techniques. We demonstrate the potential of our approach with a simple example.

Original languageEnglish (US)
Title of host publicationComputer Vision – ECCV 1996 - 4th European Conference on Computer Vision, Proceedings
EditorsBernard Buxton, Roberto Cipolla
PublisherSpringer Verlag
Pages82-93
Number of pages12
ISBN (Print)3540611231, 9783540611233
DOIs
StatePublished - 1996
Event4th European Conference on Computer Vision, ECCV 1996 - Cambridge, United Kingdom
Duration: Apr 15 1996Apr 18 1996

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1065
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other4th European Conference on Computer Vision, ECCV 1996
CountryUnited Kingdom
CityCambridge
Period4/15/964/18/96

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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    Simoncelli, E. P., & Farid, H. (1996). Direct differential range estimation using optical masks. In B. Buxton, & R. Cipolla (Eds.), Computer Vision – ECCV 1996 - 4th European Conference on Computer Vision, Proceedings (pp. 82-93). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1065). Springer Verlag. https://doi.org/10.1007/3-540-61123-1_129