Online view sampling for estimating depth from light fields

Changil Kim, Kartic Subr, Kenny Mitchell, Alexander Sorkine-Hornung, Markus Gross

Research output: Contribution to conferencePaper

9 Citations (Scopus)
33 Downloads (Pure)

Abstract

Geometric information such as depth obtained from light fields
finds more applications recently. Where and how to sample
images to populate a light field is an important problem to
maximize the usability of information gathered for depth reconstruction.
We propose a simple analysis model for view
sampling and an adaptive, online sampling algorithm tailored
to light field depth reconstruction. Our model is based on the
trade-off between visibility and depth resolvability for varying
sampling locations, and seeks the optimal locations that best
balance the two conflicting criteria.
Original languageEnglish
Publication statusPublished - 23 Sep 2015
Event22nd IEEE International Conference on Image Processing 2015 - Quebec City, Canada
Duration: 27 Sep 201530 Sep 2015
Conference number: 22

Conference

Conference22nd IEEE International Conference on Image Processing 2015
Abbreviated titleICIP 2015
CountryCanada
CityQuebec City
Period27/09/1530/09/15

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