Impact of non-linear distortion on learning based approaches for depth estimation

Julie Buquet; Jinsong Zhang; Patrice Roulet; Simon Thibault; Jean-François Lalonde

doi:10.1364/3D.2021.3W5A.5

OSA Imaging and Applied Optics Congress 2021 (3D, COSI, DH, ISA, pcAOP)
OSA Technical Digest (Optica Publishing Group, 2021),
paper 3W5A.5
•https://doi.org/10.1364/3D.2021.3W5A.5

Impact of non-linear distortion on learning based approaches for depth estimation

Julie Buquet, Jinsong Zhang, Patrice Roulet, Simon Thibault, and Jean-François Lalonde

3D Image Acquisition and Display: Technology, Perception and Applications 2021

Washington, DC United States
19–23 July 2021
ISBN: 978-1-943580-89-7

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3D Sensing and Reconstruction (3W5A)

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J. Buquet, J. Zhang, P. Roulet, S. Thibault, and J. Lalonde, "Impact of non-linear distortion on learning based approaches for depth estimation," in OSA Imaging and Applied Optics Congress 2021 (3D, COSI, DH, ISA, pcAOP), H. Hua, B. Javidi, M. Martinez-Corral, O. Matoba, A. Stern, S. Thibault, T. Alieva, J. Ke, F. Willomitzer, F. Okten, P. Silveira, P. Banerjee, E. Stoykova, D. Chu, J. Park, F. Imai, C. Joo, M. Digman, D. Gardner, S. Gladysz, D. LeMaster, S. Basu, and O. Korotkova, eds., OSA Technical Digest (Optica Publishing Group, 2021), paper 3W5A.5.

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Abstract

In this work, we evaluate the impact of non-linear distortion on learning based approaches for depth estimation. We use real wide angle images with locally increased resolutions to see how it compares with perspective images.

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