Face Recognition Using Discriminate Analysis and Canonical Correlations

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Provided by: International Journal on Computer Science and Technology (IJCST)
Topic: Security
Format: PDF
The authors address the problem of comparing sets of images for object recognition, where the sets may represent variations in an object's appearance due to changing camera pose and lighting conditions. Canonical Correlations (also known as principal or canonical angles), which can be thought of as the angles between two d-dimensional subspaces, have recently attracted attention for image set matching. Canonical correlations offer many benefits in accuracy, efficiency and robustness compared to the two main classical methods: parametric distribution-based and nonparametric sample-based matching of sets.
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