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On-line Learning of Mutually Orthogonal Subspaces for Face Recognition by Image Sets

8 years 7 months ago
On-line Learning of Mutually Orthogonal Subspaces for Face Recognition by Image Sets
—We address the problem of face recognition by matching image sets. Each set of face images is represented by a subspace (or linear manifold) and recognition is carried out by subspace-to-subspace matching. In this paper, 1) a new discriminative method that maximises orthogonality between subspaces is proposed. The method improves the discrimination power of the subspace angle based face recognition method by maximizing the angles between different classes. 2) We propose a method for on-line updating the discriminative subspaces as a mechanism for continuously improving recognition accuracy. 3) A further enhancement called locally orthogonal subspace method is presented to maximise the orthogonality between competing classes. Experiments using 700 face image sets have shown that the proposed method outperforms relevant prior art and effectively boosts its accuracy by online learning. It is shown that the method for online learning delivers the same solution as the batch computation a...
Tae-Kyun Kim, Josef Kittler, Roberto Cipolla
Added 31 Jan 2011
Updated 31 Jan 2011
Type Journal
Year 2010
Where TIP
Authors Tae-Kyun Kim, Josef Kittler, Roberto Cipolla
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