Manifold pursuit: A new approach to appearance based recognition

Amnon Shashua*, Anat Levin, Shai Avidan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

52 Scopus citations


Manifold Pursuit (MP) extends Principal Component Analysis to be invariant to a desired group of image-plane transformations of an ensemble of un-aligned images. We derive a simple technique for projecting a misaligned target image onto the linear subspace defined by the superpositions of a collection of model images. We show that it is possible to generate a fixed projection matrix which would separate the projected image into the aligned projected target and a residual image which accounts for the mis-alignment. An iterative procedure is then introduced for eliminating the residual image and leaving the correct aligned projected target image. Taken together, we demonstrate a simple and effective technique for obtaining invariance to image-plane transformations within a linear dimensionality reduction approach.

Original languageAmerican English
Pages (from-to)590-594
Number of pages5
JournalProceedings - International Conference on Pattern Recognition
Issue number3
StatePublished - 2002


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