Robust 3D-3D pose estimation

Abstract

The authors focus on the robust 3D-3D single and multiple pose estimation problems. The robust 3D-3D single pose estimation problem was formulated by R. M. Haralick et al. (1989) as a general regression in terms of a contaminated Gaussian error noise model. The robust 3D-3D multiple pose estimation problem appears much more difficult. This problem is formulated as a series of general regressions involving successively decreasing data size, with each regression related to one particular pose of interest. Since the first few regressions may carry a highly contaminated Gaussian error noise model, a very robust estimator called the MF-estimator, given by X. Zhuang et al. (1992), is used to solve each regression for each desired pose estimation. Computer experiments with real imagery and simulated data were conducted and results are promising. >