Vector transformation for indexing, similarity search and classification
US8165414B1 · kind B1 · utility
Assignee
Inventor
Key dates
| Filing date | Nov 3, 2011 |
| Grant date | Apr 24, 2012 |
| Priority date | — |
| Expiry date | Nov 3, 2031 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/513
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A feature vector is encoded into a sparse binary vector. The feature vector is retrieved, for example from storage or a feature vector generator. The feature vector represents a media object or other data object. One or more permutations are generated, the dimensionality of the generated permutations equivalent to the dimensionality of the feature vector. The permutations may be generated randomly or formulaically. The feature vector is permuted with the one or more permutations, creating one or more permuted feature vectors. The permuted feature vectors are truncated according to a selected window size. The indexes representing the maximum values of the permuted feature vectors are identified and encoded using one-hot encoding, producing one or more sparse binary vectors. The sparse binary vectors may be concatenated into a single sparse binary vector and stored. The sparse binary vector may be used in the similarity search, indexing or categorization of media objects.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.