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21 August 2020 Analysis of algebraic and geometric distances for projective transformation estimation
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Abstract
Estimation of projective transformations is an essential process in modern vision-based applications. Usually, the provided experimental point correspondences required to estimate the projective transformations are corrupted with random noise. Thus, for an accurate estimation of the actual projective transformation, a robust optimization criterion must be employed. In this work, we analyze a two-step estimation approach for robust projective transformation estimation. First, the algebraic distance is employed to obtain an initial guess. Then, the geometric distance is used to refine this initial guess. Three geometric-based refining methods are evaluated, namely, the one-image error, the symmetric-transfer error, and reprojection. The obtained results confirm a high accuracy and robustness of the analyzed approach.
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© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Obed I. Rios-Orellana, Rigoberto Juarez-Salazar, and Victor H. Diaz-Ramirez Sr. "Analysis of algebraic and geometric distances for projective transformation estimation", Proc. SPIE 11509, Optics and Photonics for Information Processing XIV, 115090A (21 August 2020); https://doi.org/10.1117/12.2569761
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