Self learning face recognition using depth based tracking for database generation and update
US8855369B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 22, 2012 |
| Grant date | Oct 7, 2014 |
| Priority date | — |
| Expiry date | Dec 4, 2032 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/10016
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Face recognition training database generation technique embodiments are presented that generally involve collecting characterizations of a person's face that are captured over time and as the person moves through an environment, to create a training database of facial characterizations for that person. As the facial characterizations are captured over time, they are will represent the person's face as viewed from various angles and distances, different resolutions, and under different environmental conditions (e.g., lighting and haze conditions). Further, over a long period of time where facial characterizations of a person are collected periodically, these characterizations can represent an evolution in the appearance of the person. This produces a rich training resource for use in face recognition systems. In addition, since a person's face recognition training database can be established before it is needed by a face recognition system, once employed, the training will be quicker.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.