Regularized vector field learning with sparse approximation for mismatch removal
A sparse approximation is presented for vector-valued regularized least-squares. We derive a bound for the sparse approximation. Based on it, we give a new robust vector field learning algorithm called SparseVFC. We apply SparseVFC to mismatch removal and it achieves state-of-the-art performance. The proposed method has linear time and space complexities in the scale of samples.
regularization vector field learning sparse approximation mismatch removal reproducing kernel hilbert space outlier