Merging and Splitting Eigenspace Models
Peter Hall, David Marshall, and Ralph Martin

Adding Eigenspaces
We present new deterministic methods that given two eigenspace models - each representing a set of n-dimensional observations- will:
  1. merge the models to yield a representation of the union of the sets and
  2. split one model from another to represent the difference between the sets.
As this is done, we accurately keep track of the mean. Here, we give a theoretical derivation of the methods, empirical results relating to the efficiency and accuracy of the techniques, and three general applications, including the construction of Gaussian mixture models that are dynamically updateable.

Key Papers

Merging and Splitting Eigenspace Models (PDF), P. M. Hall, A. D. Marshall, R. R. Martin IEEE PAMI 22 (9), pp 1042-1049, 2000

Adding and subtracting eigenspaces with eigenvalue decomposition and singular value decomposition (PDF), P.M. Hall, A.D. Marshall and R.R. Martin, Hall, P., Marshall, D. and Martin, R. Image and Vision Computing, Volume 20, Issues 13-14, December 2002, pp 1009-1016 ISSN: 0262-8856

Adding and Subtracting Eigenspaces (PDF), P.M. Hall, A.D. Marshall and R.R. Martin, Proceeding of the 10th British Machine Vision Conference, 13-17 Sept. 1999, Univ. of Nottingham. pp 453-462 ISBN 1-901725-09-X.

Incremental Eigenanalysis for Classification (PDF), P.M. Hall, A.D. Marshall and R.R. Martin, Proceedings of the British Machine Vision Conference - BMVC 98, Sept 1998. Vol. 1, pp 286-295, Eds. P.H. Lewis and M.S.Nixon, ISBN 1-901725-04-9, 1998

Other Links

A full list of my publications and some downloadable papers are available ONLINE.