Sparse learning approach to the problem of robust estimation of camera locations

摘要

In this paper, we propose a new approach-inspired by the recent advances in the theory of sparse learning-to the problem of estimating camera locations when the internal parameters and the orientations of the cameras are known. Our estimator is defined as a Bayesian maximum a posteriori with multivariate Laplace prior on the vector describing the outliers. This leads to an estimator in which the fidelity to the data is measured by the L