Conjugate gradient on Grassmann manifolds for robust subspace estimation
Image and Vision Computing
Generalised relaxed Radon transform (GR2T) for robust inference
Pattern Recognition
A simultaneous sample-and-filter strategy for robust multi-structure model fitting
Computer Vision and Image Understanding
| Hi-index | 0.00 |
We introduce a robust estimator called generalized projection based M-estimator (gpbM) which does not require the user to specify any scale parameters. For multiple inlier structures, with different noise covariances, the estimator iteratively determines one inlier structure at a time. Unlike pbM, where the scale of the inlier noise is estimated simultaneously with the model parameters, gpbM has three distinct stages-scale estimation, robust model estimation and inlier/outlier dichotomy. We evaluate our performance on challenging synthetic data, face image clustering upto ten different faces from Yale Face Database B and multi-body projective motion segmentation problem on Hopkins155 dataset. Results of state-of-the-art methods are presented for comparison.