Abstract: A system for clustering data comprises a database for storing a plurality of data items, a clustering unit comprising components operable to receive and cluster the plurality of data items, and output clustered data items. A method of clustering data comprises receiving a plurality of data items from a database; computing distances between each pair of data items in the plurality of data items; until a stopping criterion is reached, identifying key elements, merging data items not identified as key elements with the nearest key elements, updating the computed distances; once the stopping criterion is reached, outputting cluster identities of the plurality of data items.

Abstract: A system for clustering data comprises a database for storing a plurality of data items, a clustering unit comprising components operable to receive and cluster the plurality of data items, and output clustered data items. A method of clustering data comprises receiving a plurality of data items from a database; computing distances between each pair of data items in the plurality of data items; until a stopping criterion is reached, identifying key elements, merging data items not identified as key elements with the nearest key elements, updating the computed distances; once the stopping criterion is reached, outputting cluster identities of the plurality of data items.

Abstract: A system for clustering data comprises a database for storing a plurality of data items, a clustering unit comprising components operable to receive and cluster the plurality of data items, and output clustered data items. A method of clustering data comprises receiving a plurality of data items from a database; computing distances between each pair of data items in the plurality of data items; until a stopping criterion is reached, identifying key elements, merging data items not identified as key elements with the nearest key elements, updating the computed distances; once the stopping criterion is reached, outputting cluster identities of the plurality of data items.

Abstract: A system and method for generating a descriptor for a face is provided. The descriptor is operable to generate information about a given region in a face image to enable face recognition. The descriptor provided herein is a low dimension relative to many existing descriptors providing similar face recognition accuracy. In another aspect, a system and method for face recognition is provided.

Abstract: A system for clustering data comprises a database for storing a plurality of data items, a clustering unit comprising components operable to receive and cluster the plurality of data items, and output clustered data items. A method of clustering data comprises receiving a plurality of data items from a database; computing distances between each pair of data items in the plurality of data items; until a stopping criterion is reached, identifying key elements, merging data items not identified as key elements with the nearest key elements, updating the computed distances; once the stopping criterion is reached, outputting cluster identities of the plurality of data items.

Abstract: A system and method for generating a descriptor for a face is provided. The descriptor is operable to generate information about a given region in a face image to enable face recognition. The descriptor provided herein is a low dimension relative to many existing descriptors providing similar face recognition accuracy. In another aspect, a system and method for face recognition is provided.

Abstract: A system and method for performing object or context-based categorization of an image is described. A descriptor for image regions, which is represented by a histogram of oriented uniform patterns, is described. The descriptor is compared to descriptors of other images to determine a similarity score that accounts for distinctiveness, reducing perceptual aliasing. Additionally, a kernel alignment process considers only the descriptors that are determined to be most informative.