Memoirs of the Faculty of Engineering, Okayama University
Published by Faculty of Enginerring, Okayama University

<Formerly known as>
Memoirs of the School of Engineering, Okayama University

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High Accuracy Homography Computation without Iterations

金谷 健一 Department of Computer Science Okayama University
Niitsuma Hirotaka Department of Computer Science Okayama University
Rangrajan Prasanna Department of Electrical Engineering Southern Methodist University
We present highly accurate least-squares (LS) alternatives to the theoretically optimal maximum likelihood (ML) estimator for homographies between two images. Unlike ML, our estimators are non-iterative and yield solutions even in the presence of large noise. By rigorous error analysis, we derive a “hyperaccurate” estimator which is unbiased up to second order noise terms. Then, we introduce a computational simplification, which we call “Taubin approximation”, without incurring a loss in accuracy. We experimentally demonstrate that our estimators have accuracy surpassing the traditional LS estimator and comparable to the ML estimator.