This paper explores a recently proposed and rarely reported subspace learning method, Spectral Regression Discriminant Analysis (SRDA) [1, 2], on silhouette based human action rec...
PCA-SIFT is an extension to SIFT which aims to reduce SIFT’s high dimensionality (128 dimensions) by applying PCA to the gradient image patches. However PCA is not a discriminati...
This paper proposes a general method for improving image descriptors using discriminant projections. Two methods based on Linear Discriminant Analysis have been recently introduce...
Current approaches to automated analysis have focused on a small set of prototypic expressions (e.g., joy or anger). Prototypic expressions occur infrequently in everyday life, ho...
Jeffrey F. Cohn, Adena J. Zlochower, James Jenn-Ji...
It is well known that exploiting label correlations is important for multi-label learning. Existing approaches typically exploit label correlations globally, by assuming that the ...