Abstract We develop a distance metric for clustering and classification algorithms which is invariant to affine transformations and includes priors on the transformation parameters...
There are several pieces of information that can be utilized in order to improve the efficiency of similarity searches on high-dimensional data. The most commonly used information...
We propose an efficient algorithm to find the exact nearest neighbor based on the Euclidean distance for largescale computer vision problems. We embed data points nonlinearly on...
In this paper we describe an approach that uses a combination of visual and audio features to cluster shots belonging to the same person together in video programs. We use color h...
Various problems in machine learning, databases, and statistics involve pairwise distances among a set of objects. It is often desirable for these distances to satisfy the propert...