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Authors: Mara Pistellato ; Filippo Bergamasco ; Andrea Albarelli ; Luca Cosmo ; Andrea Gasparetto and Andrea Torsello

Affiliation: DAIS, Ca’Foscari University of Venice, Via Torino 155, Venice and Italy

Keyword(s): Phase Shift, Structured Light, 3D Reconstruction.

Related Ontology Subjects/Areas/Topics: Applications ; Cardiovascular Imaging and Cardiography ; Cardiovascular Technologies ; Health Engineering and Technology Applications ; Pattern Recognition ; Signal Processing ; Software Engineering

Abstract: Phase-shift is one of the most effective techniques in 3D structured-light scanning for its accuracy and noise resilience. However, the periodic nature of the signal causes a spatial ambiguity when the fringe periods are shorter than the projector resolution. To solve this, many techniques exploit multiple combined signals to unwrap the phases and thus recovering a unique consistent code. In this paper, we study the phase estimation and unwrapping problem in a stochastic context. Assuming the acquired fringe signal to be affected by additive white Gaussian noise, we start by modelling each estimated phase as a zero-mean Wrapped Normal distribution with variance σ̄2. Then, our contributions are twofolds. First, we show how to recover the best projector code given multiple phase observations by means of a ML estimation over the combined fringe distributions. Second, we exploit the Cramér-Rao bounds to relate the phase variance σ̄2 to the variance of the observed signal, that can be eas ily estimated online during the fringe acquisition. An extensive set of experiments demonstrate that our approach outperforms other methods in terms of code recovery accuracy and ratio of faulty unwrappings. (More)


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Paper citation in several formats:
Pistellato, M.; Bergamasco, F.; Albarelli, A.; Cosmo, L.; Gasparetto, A. and Torsello, A. (2019). Stochastic Phase Estimation and Unwrapping. In Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-351-3; ISSN 2184-4313, SciTePress, pages 200-209. DOI: 10.5220/0007389402000209

author={Mara Pistellato. and Filippo Bergamasco. and Andrea Albarelli. and Luca Cosmo. and Andrea Gasparetto. and Andrea Torsello.},
title={Stochastic Phase Estimation and Unwrapping},
booktitle={Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - ICPRAM},


JO - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Stochastic Phase Estimation and Unwrapping
SN - 978-989-758-351-3
IS - 2184-4313
AU - Pistellato, M.
AU - Bergamasco, F.
AU - Albarelli, A.
AU - Cosmo, L.
AU - Gasparetto, A.
AU - Torsello, A.
PY - 2019
SP - 200
EP - 209
DO - 10.5220/0007389402000209
PB - SciTePress