US Patent Number
7725484
Publication Date
5-25-2010
Abstract
An image retrieval technique employing a novel hierarchical feature/descriptor vector quantizer tool—‘vocabulary tree’, of sorts comprising hierarchically organized sets of feature vectors—that effectively partitions feature space in a hierarchical manner, creating a quantized space that is mapped to integer encoding. The computerized implementation of the new technique(s) employs subroutine components, such as: A trainer component of the tool generates a hierarchical quantizer, Q, for application/use in novel image-insertion and image-query stages. The hierarchical quantizer, Q, tool is generated by running k-means on the feature (a/k/a descriptor) space, recursively, on each of a plurality of nodes of a resulting quantization level to ‘split’ each node of each resulting quantization level. Preferably, training of the hierarchical quantizer, Q, is performed in an ‘offline’ fashion.
Assignees
University of Kentucky Research Foundation (UKRF), Lexington, KY (US)
Application Number
11/602,419
Filing Date
11/20/2006
Recommended Citation
Nistér, David and Stewénius, Henrik, "Scalable Object Recognition Using Hierarchical Quantization with a Vocabulary Tree" (2010). Center for Visualization and Virtual Environments Faculty Patents. 1.
https://uknowledge.uky.edu/cvve_patents/1
