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Robust Estimation of Rotation Angles from Image Sequences Using the Annealing M-Estimator

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Abstract

A robust method is presented for computing rotation angles of image sequences from a set of corresponding points containing outliers. Assuming known rotation axis, a least-squares (LS) solution are derived to compute the rotation angle from a clean data set of point correspondences. Since clean data is not guaranteed, we introduce a robust solution, based on the M-estimator, to deal with outliers. Then we present an enhanced robust algorithm, called the annealing M-estimator (AM-estimator), for reliable robust estimation. The AM-estimator has several attractive advantages over the traditional M-estimator: By definition, the AM-estimator involves neither scale estimator nor free parameters and hence avoids instabilities therein. Algorithmically, it uses a deterministic annealing technique to approximate the global solution regardless of the initialization. Experimental results are presented to compare the performance of the LS, M- and AM-estimators for the angle estimation. Experiments show that in the presence of outliers, the M-estimator outperforms the LS estimator and the AM-estimator outperforms the M-estimator.

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Authors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, 639798

    Stan Z. Li, Han Wang & William Y.C. Soh

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  1. Stan Z. Li
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  2. Han Wang
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  3. William Y.C. Soh
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Li, S.Z., Wang, H. & Soh, W.Y. Robust Estimation of Rotation Angles from Image Sequences Using the Annealing M-Estimator. Journal of Mathematical Imaging and Vision 8, 181–192 (1998). https://doi.org/10.1023/A:1008281429730

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