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

Authors:
Stan Z. Li;Han Wang;William Y. C. Soh
Affiliations:
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798.;School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798.;School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798.
Venue:
Journal of Mathematical Imaging and Vision
Year:
1998

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Abstract

A robust method is presented for computing rotation angles of imagesequences from a set of corresponding points containing outliers. Assumingknown rotation axis, a least-squares (LS) solution are derived to computethe rotation angle from a clean data set of point correspondences. Sinceclean data is not guaranteed, we introduce a robust solution, based on theM-estimator, to deal with outliers. Then we present an enhanced robustalgorithm, called the annealing M-estimator (AM-estimator), for reliablerobust estimation. The AM-estimator has several attractive advantages overthe traditional M-estimator: By definition, the AM-estimator involvesneither scale estimator nor free parameters and hence avoids instabilitiestherein. Algorithmically, it uses a deterministic annealing technique toapproximate 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 thepresence of outliers, the M-estimator outperforms the LS estimator and theAM-estimator outperforms the M-estimator.