arXiv Computer Vision By Osman Ali (Manufacturing Metrology Team, University of Nottingham, Nottingham, United Kingdom), Xiangjun Kong (Manufacturing Metrology Team, University of Nottingham, Nottingham, United Kingdom), Tibebe Yalew (Manufacturing Metrology Team, University of Nottingham, Nottingham, United Kingdom), Waiel Elmadih (Taraz Metrology Ltd., Nottingham, United Kingdom), Samanta Piano (Manufacturing Metrology Team, University of Nottingham, Nottingham, United Kingdom)

RACE-FPP: A Robust AI-assisted Characterisation Enhancement for Fringe Projection Profilometry

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arXiv Machine Learning
Jul 10

Diagnosing Shape-Prior Shortcuts in Long-Range Single-Shot Fringe Projection Profilometry

arXiv:2606. 17093v2 Announce Type: replace Abstract: Learning-based single-shot fringe projection profilometry (FPP) has been studied almost entirely at close range, and the networks used are evaluated only on aggregate error, leaving open whether they recover depth from fringe phase or from object-level shape cues that correlate with depth.

By Adam Haroon, Anush Lakshman, Cody Fleming, Beiwen Li