Subspace Estimation Using Projection Based M-Estimators over Grassmann Manifolds

Abstract. We propose a solution to the problem of robust subspace estimation using the projection based M-estimator. The new method handles more outliers than inliers, does not require a user defined scale of the noise affecting the inliers, handles noncentered data and nonorthogonal subspaces. Other robust methods like RANSAC, use an input for the scale, while methods for subspace segmentation, like GPCA, are not robust. Synthetic data and three real cases of multibody factorization show the superiority of our method, in spite of user independence.

• Type: Conference
• Year: 2006
• Where: ECCV
• Authors: Raghav Subbarao, Peter Meer
• Keywords: Computer Vision, ECCV 2006, Multibody Factorization, Other Robust Methods, Robust Subspace Estimation, Subspace Segmentation, User Defined Scale