A comparative review of optical flow estimation methods for computer-generated holograms

Nabil Madali; Antonin Gilles; Patrick Gioia; Luce Morin

doi:10.1117/12.3015873

18 June 2024 A comparative review of optical flow estimation methods for computer-generated holograms

Nabil Madali, Antonin Gilles, Patrick Gioia, Luce Morin

Proceedings Volume 12998, Optics, Photonics, and Digital Technologies for Imaging Applications VIII; 129980F (2024) https://doi.org/10.1117/12.3015873
Event: SPIE Photonics Europe, 2024, Strasbourg, France

Abstract

Accurately estimating 3D optical flow in computer-generated holography poses a challenge due to the scrambling of 3D scene information during hologram acquisition. Therefore, to estimate the scene motion between consecutive frames, the scene geometry should be recovered first. Recent studies have demonstrated that a 3D RGB-D representation can be extracted from an input hologram with relatively low error under well-chosen numerical reconstruction parameters. However, limited attention has been given to how the produced error can impact the flow estimation algorithms. Therefore, in this study, we evaluate different learning/non-learning methodologies for recovering 3D scene geometry. Next, we analyze the types of distortions produced by these methods and attempt to minimize estimation error using spatial and temporal constraints. Finally, we compare the performance of several state-of-the-art methods to estimate the 3D optical flow vectors on the recovered sequence of RGB-D images.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Nabil Madali, Antonin Gilles, Patrick Gioia, and Luce Morin "A comparative review of optical flow estimation methods for computer-generated holograms", Proc. SPIE 12998, Optics, Photonics, and Digital Technologies for Imaging Applications VIII, 129980F (18 June 2024); https://doi.org/10.1117/12.3015873

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