Object Classification in Photon-Starved Conditions using 3D Integral Imaging: Performance Comparison Between Visible and Longwave Infrared Imaging

P. Wani; K. Usmani; G. Krishnan; T. O’Connor; B. Javidi

doi:10.1364/3D.2021.3Th4D.3

OSA Imaging and Applied Optics Congress 2021 (3D, COSI, DH, ISA, pcAOP)
OSA Technical Digest (Optica Publishing Group, 2021),
paper 3Th4D.3
•https://doi.org/10.1364/3D.2021.3Th4D.3

Object Classification in Photon-Starved Conditions using 3D Integral Imaging: Performance Comparison Between Visible and Longwave Infrared Imaging

P. Wani, K. Usmani, G. Krishnan, T. O’Connor, and B. Javidi

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 Displays (3Th4D)

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P. Wani, K. Usmani, G. Krishnan, T. O’Connor, and B. Javidi, "Object Classification in Photon-Starved Conditions using 3D Integral Imaging: Performance Comparison Between Visible and Longwave Infrared Imaging," 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 3Th4D.3.

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Abstract

We present a method for object detection and classification in photon-starved conditions and occluded environments using passive 3D integral imaging with convolution neural networks. Performance will be compared between visible and infra-red range image sensors.

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