ABSTRACT
In [133], clustered blockwise PCA takes advantage of the spatiotemporal correlation and localized frequency variations that are typically found in data sets. Therefore, the algorithm not only achieves greater efficiency in the resulting representation of the visual data, but also successfully scales PCA to handle large data sets.
