Generalized Projection Based M-Estimator: Theory and Applications

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.

• Type: Journal
• Year: 2011
• Where: CVPR
• Authors: Sushil Mittal, Saket Anand, Peter Meer
• Keywords: Computer Vision, CVPR 2011, Inlier Structure, Multi-body Projective Motion, Robust Model Estimation