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Re-weighting and 1-Point RANSAC-Based P nP Solution to Handle Outliers

Institution:
Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Publisher:
IEEE Computer Society
Publication Date:
Dec-2019
Journal:
IEEE Trans Pattern Anal Mach Intell
Volume Number:
41
Issue Number:
12
Pages:
3022-33
Citation:
IEEE Trans Pattern Anal Mach Intell. 2019 Dec;41(12):3022-33.
PubMed ID:
31689179
PMCID:
PMC6857708
Appears in Collections:
NCIGT, SPL
Sponsors:
P41 EB015898/EB/NIBIB NIH HHS/United States
R01 EB025964/EB/NIBIB NIH HHS/United States
Generated Citation:
Zhou H., Zhang T., Jagadeesan J. Re-weighting and 1-Point RANSAC-Based P nP Solution to Handle Outliers. IEEE Trans Pattern Anal Mach Intell. 2019 Dec;41(12):3022-33. PMID: 31689179. PMCID: PMC6857708.
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The ability to handle outliers is essential for performing the perspective- n-point (P nP) approach in practical applications, but conventional RANSAC+P3P or P4P methods have high time complexities. We propose a fast P nP solution named R1PP nP to handle outliers by utilizing a soft re-weighting mechanism and the 1-point RANSAC scheme. We first present a P nP algorithm, which serves as the core of R1PP nP, for solving the P nP problem in outlier-free situations. The core algorithm is an optimal process minimizing an objective function conducted with a random control point. Then, to reduce the impact of outliers, we propose a reprojection error-based re-weighting method and integrate it into the core algorithm. Finally, we employ the 1-point RANSAC scheme to try different control points. Experiments with synthetic and real-world data demonstrate that R1PP nP is faster than RANSAC+P3P or P4P methods especially when the percentage of outliers is large, and is accurate. Besides, comparisons with outlier-free synthetic data show that R1PP nP is among the most accurate and fast P nP solutions, which usually serve as the final refinement step of RANSAC+P3P or P4P. Compared with REPP nP, which is the state-of-the-art P nP algorithm with an explicit outliers-handling mechanism, R1PP nP is slower but does not suffer from the percentage of outliers limitation as REPP nP.