6533b830fe1ef96bd12972a3
RESEARCH PRODUCT
Null Space Based Image Recognition Using Incremental Eigendecomposition
Wladimiro Diaz-villanuevaKaterine Diaz-chitoFrancesc J. Ferrisubject
Training setbusiness.industryComputationContext (language use)Pattern recognitionRule-based systemLinear subspaceDiscriminative modelComputer visionArtificial intelligencebusinessOrthogonalizationEigendecomposition of a matrixMathematicsdescription
An incremental approach to the discriminative common vector (DCV) method for image recognition is considered. Discriminative projections are tackled in the particular context in which new training data becomes available and learned subspaces may need continuous updating. Starting from incremental eigendecomposition of scatter matrices, an efficient updating rule based on projections and orthogonalization is given. The corresponding algorithm has been empirically assessed and compared to its batch counterpart. The same good properties and performance results of the original method are kept but with a dramatic decrease in the computation needed.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2011-01-01 |