The DOI matches its Crossref record; 79 of the 79 references it cites were found in a registry or an index.
Status, challenges, and future perspectives of fringe projection profilometry
Open accessAbstract
Abstract As one of the most popular techniques for non-contact three-dimensional (3D) sensing/imaging, fringe projection profilometry (FPP) has been growing rapidly over the past decades partially because of the improved speed of computing devices and reduced cost of hardware. 3D optical sensing has started being an integral part of our daily lives such as Face ID enabled by 3D sensors on smart phones. The impact of such techniques can be even greater with the ever-growing artificial intelligent (AI), machine learning, smart manufacturing, robotics as well as other fields. However, there are still fundamental challenges to be tackled to make such advanced optical sensing techniques ubiquitous. This paper presents the current status of FPP techniques, the major challenges still facing in the field, and our perspectives on the future of FPP techniques.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Multiple View Geometry in Computer Vision
Hartley, R., & Zisserman, A. (2004) · doi:10.1017/cbo9780511811685 · Cited by 21,070
A flexible new technique for camera calibration
Zhang, Z. (2000) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.888718 · Cited by 15,004
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
Scharstein, D., & Szeliski, R. (2002) · International Journal of Computer Vision · doi:10.1023/a:1014573219977 · Cited by 6,740
Tsai, R. (1987) · IEEE Journal on Robotics and Automation · doi:10.1109/jra.1987.1087109 · Cited by 5,838
Multiple View Geometry in Computer Vision
(2001) · Kybernetes · doi:10.1108/k.2001.30.9_10.1333.2 · Cited by 3,336
(2007) · Wiley eBooks · doi:10.1002/9780470135976 · Cited by 2,092
Two-Dimensional Phase Unwrapping: Theory, Algorithms, and Software
Ghiglia, D. C., & Pritt, M. D. (1998) · Medical Entomology and Zoology · Cited by 2,031
Fourier transform profilometry for the automatic measurement of 3-D object shapes
Takeda, M., & Mutoh, K. (1983) · Applied Optics · doi:10.1364/ao.22.003977 · Cited by 1,855
Phase shifting algorithms for fringe projection profilometry: A review
Zuo, C., Feng, S., Huang, L., Tao, T., Yin, W., & Chen, Q. (2018) · Optics and Lasers in Engineering · doi:10.1016/j.optlaseng.2018.04.019 · Cited by 1,291
Recent progresses on real-time 3D shape measurement using digital fringe projection techniques
Zhang, S. (2010) · Optics and Lasers in Engineering · doi:10.1016/j.optlaseng.2009.03.008 · Cited by 999
Self-citation
Metadata
- Authors
- Xu, J., & Zhang, S.
- Venue
- Optics and Lasers in Engineering
- Publisher
- Elsevier BV
- Published
- 2020-12
- Volume
- 135
- Pages
- 106193
- ISSN
- 0143-8166 (ISSN-L)
- OpenAlex
- W3033101048
- Cited by
- 469
- References
- 79
- FWCI
- 19.47
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Status, challenges, and future perspectives of fringe projection profilometry. https://app.cochat.ai/papers/10.1016/j.optlaseng.2020.106193
- The paper
- Xu, J., & Zhang, S. (2020). Status, challenges, and future perspectives of fringe projection profilometry. Optics and Lasers in Engineering. https://doi.org/10.1016/j.optlaseng.2020.106193
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
