Subspace Estimation Using Projection Based M-Estimators over Grassmann Manifolds

  • Raghav Subbarao
  • Peter Meer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3951)


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.


Parallel Transport Conjugate Gradient Algorithm Grassmann Manifold Motion Segmentation Elemental Subset 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Raghav Subbarao
    • 1
  • Peter Meer
    • 1
  1. 1.Department of Electrical and Computer EngineeringRutgers UniversityPiscatawayUSA

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