Face recognition and image search system using sparse feature vectors, compact binary vectors, and sub-linear search
US10482336B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 4, 2017 |
| Grant date | Nov 19, 2019 |
| Priority date | — |
| Expiry date | Dec 6, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V40/50
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods are provided for performing automated face recognition and comparison. An input image of a face may be received and cropped, and the image may be processed through a deep neural network (DNN) to produce a k-dimensional feature vector. The k-dimensional feature vector may be converted to a k-dimensional binary vector by transforming each value in the vector to either 1 or 0. To search for nearest matches of the image in a database of gallery images of faces, the system may compare sub-strings of the binary vector to hash tables created from sub-strings of the gallery images, enabling sub-linear searching that allows locating the closest matches from among the entire gallery without requiring an exhaustive linear search of the entire gallery.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.