This paper concerns approximate nearest neighbor searching algorithms, which have become increasingly important, especially in high dimensional perception areas such as computer v...
Ting Liu, Andrew W. Moore, Alexander G. Gray, Ke Y...
Abstract—In classical image classification approaches, lowlevel features have been used. But the high dimensionality of feature spaces poses a challenge in terms of feature selec...
Rajeev Agrawal, Changhua Wu, William I. Grosky, Fa...
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...
—On a stream of two dimensional data items (x, y) where x is an item identifier, and y is a numerical attribute, a correlated aggregate query requires us to first apply a selec...
This paper proposes the use of a new symmetry property based on proximity of the median moments in the wavelet domain. The method divides a given frame into 16 equally sized blocks...