The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
A Robust O(n) Solution to the Perspective-n-Point Problem
Abstract
We propose a noniterative solution for the Perspective-n-Point ({\rm P}n{\rm P}) problem, which can robustly retrieve the optimum by solving a seventh order polynomial. The central idea consists of three steps: 1) to divide the reference points into 3-point subsets in order to achieve a series of fourth order polynomials, 2) to compute the sum of the square of the polynomials so as to form a cost function, and 3) to find the roots of the derivative of the cost function in order to determine the optimum. The advantages of the proposed method are as follows: First, it can stably deal with the planar case, ordinary 3D case, and quasi-singular case, and it is as accurate as the state-of-the-art iterative algorithms with much less computational time. Second, it is the first noniterative {\rm P}n{\rm P} solution that can achieve more accurate results than the iterative algorithms when no redundant reference points can be used (n\le 5). Third, large-size point sets can be handled efficiently because its computational complexity is O(n).
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Cites
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EPnP: An Accurate O(n) Solution to the PnP Problem
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Hu, Y., Hugonot, J., Fua, P., & Salzmann, M. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00350 · Cited by 333
Intraoperative 2D/3D Image Registration via Differentiable X-Ray Rendering
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“In landmark-based localization, feature extractors find correspondences between anatomical landmarks in 2D and 3D images, which are then used by a Perspective-n-Point (PnP) solver to estimate the camera pose [30, 31].”
MethodTowards Fully Automatic X-Ray to CT Registration
Esteban, J., Grimm, M., Unberath, M., Zahnd, G., & Navab, N. (2019) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-32226-7_70 · Cited by 38
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Gopalakrishnan, V., Chlorogiannis, D.-D., Abumoussa, A., Larson, A. M., Haouchine, N., Orbach, D. B., Frisken, S., Dey, N., & Golland, P. (2025) · arXiv · doi:10.48550/arxiv.2503.16309 · Cited by 13
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Metadata
- Authors
- Li, S., Xu, C., & Xie, M.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2012-07
- Volume
- 34
- Issue
- 7
- Pages
- 1444-1450
- ISSN
- 0162-8828 (ISSN-L)
- 2160-9292
- OpenAlex
- W1984667320
- Cited by
- 503
- References
- 32
- FWCI
- 13.77
- Type
- journal article
- Language
- en
- Open access
- closed
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