A Resampling Method for Computer Vision

A resampling procedure based on Efron’s bootstrap method is proposed for the robust estimation of parameters from redundant data. The procedure handles a substantial fraction of outliers, has linear complexity even for superlinear estimation problems, can be applied to any parameter estimation algorithm without modification, and is easily parallelized. The problem of estimating camera motion from instantaneous image velocities is used to illustrate the method. Simulations and results show robust and accurate results.

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