Online view sampling for estimating depth from light fields

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

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.

Citation

Kim, C., Subr, K., Mitchell, K., Sorkine-Hornung, A., & Gross, M. (2015, September). Online view sampling for estimating depth from light fields. Presented at 2015 IEEE International Conference on Image Processing (ICIP)

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 2015 IEEE International Conference on Image Processing (ICIP)
• Start Date: Sep 27, 2015
• End Date: Sep 30, 2015
• Acceptance Date: Jul 7, 2015
• Online Publication Date: Dec 10, 2015
• Publication Date: Dec 10, 2015
• Deposit Date: Dec 12, 2017
• Publicly Available Date: Dec 14, 2017
• Publisher: Institute of Electrical and Electronics Engineers
• Book Title: 2015 IEEE International Conference on Image Processing (ICIP)
• Chapter Number: n/a
• ISBN: 978-1-4799-8339-1
• DOI: https://doi.org/10.1109/icip.2015.7350981
• Keywords: Light fields, geometric information, image sampling, image reconstruction,
• Public URL: http://researchrepository.napier.ac.uk/Output/951612
• Contract Date: Dec 12, 2017